XML Full-Text Search: Challenges and Opportunities Sihem Amer-Yahia AT&T Labs – Research Jayavel Shanmugasundaram Cornell University 2 September 2005 VLDB Tutorial on XML Full-Text Search
Outline • • • Motivation Full-Text Search Languages Scoring Query Processing Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search
Motivation • XML is able to represent a mix of structured and text information. • XML applications: digital libraries, content management. • XML repositories: IEEE INEX collection, Lexis. Nexis, the Library of Congress collection. 2 September 2005 VLDB Tutorial on XML Full-Text Search
![]( "XML in Library of Congress http: //thomas. loc. gov/home/gpoxmlc 109/h 2739_ih. xml <bill-stage=")
109" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-4.jpg" alt="XML in Library of Congress http: //thomas. loc. gov/home/gpoxmlc 109/h 2739_ih. xml 109" />
XML in Library of Congress http: //thomas. loc. gov/home/gpoxmlc 109/h 2739_ih. xml 109 th CONGRESS 1 st Session H. R. 2739 IN THE HOUSE OF REPRESENTATIVES May 26, 2005 Mr. Tierney (for himself, Ms. Mc. Collum of Minnesota, Mr. George Miller of California) introduced the following bill; which was referred to the Committee on Education and the Workforce … 2 September 2005 VLDB Tutorial on XML Full-Text Search
THOMAS: Library of Congress 2 September 2005 VLDB Tutorial on XML Full-Text Search
INEX Data K 0271 10. 1041/K 0271 s-2004 IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 1041 -4347/04/$20. 00 © 2004 IEEE Published by the IEEE Computer SocietyVol. 16, No. 2 FEBRUARY2004 pp. 271 -288 A Graph-Based Approach for Timing Analysis and Refinement of OPS 5 Knowledge. Based Systemspp. 271 -288[*] Albert Mo Kim [Cheng]Senior MemberIEEEHsiu-yen Tsai Abstract— This paper examines the problem of predicting the timing behavior of knowledge-based systems for real… 2 September 2005 VLDB Tutorial on XML Full-Text Search
![]( "Example INEX Query <inex_topic_id=")
//article[about(. //abs, "data mining")]//sec[about(. , "frequent itemsets")] sections about" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-7.jpg" alt="Example INEX Query //article[about(. //abs, "data mining")]//sec[about(. , "frequent itemsets")] sections about" />
Example INEX Query //article[about(. //abs, "data mining")]//sec[about(. , "frequent itemsets")] sections about frequent itemsets from articles with abstract about data mining To be relevant, a component has to be a section about "frequent itemsets". For example, it could be about algorithms for finding frequent itemsets, or uses of frequent itemsets to generate rules. Also, the article must have an abstract about "data mining". I need this information for a paper that I am writing. It is a survey of different algorithms for finding frequent itemsets. The paper will also have a section on why we would want to find frequent itemsets. 2 September 2005 VLDB Tutorial on XML Full-Text Search
Challenges in XML FT Search • Searching over Semi-Structured Data – Users may specify a search context and return context. • Expressive Power and Extensibility – Users should be able to express complex full-text searches and combine them with structural searches. • Scores and Ranking – Users may specify a scoring condition, possibly over both full-text and structured predicates and obtain top-k results based on query relevance scores. – The language should allow for an efficient implementation. 2 September 2005 VLDB Tutorial on XML Full-Text Search
XML FT Search Definition • Context expression: XML elements searched: – pre-defined XML nodes. – XPath/XQuery queries. • Return expression: XML fragments returned: – pre-defined meaningful XML fragments. – XPath/XQuery to build answers. • Search expression: FT search conditions: – Boolean keyword search. – proximity distance, scoping, thesaurus, stop words, stemming. • Score expression: – system-defined scoring function. – user-defined scoring function. – query-dependent keyword weights. 2 September 2005 VLDB Tutorial on XML Full-Text Search
Outline • • • Motivation Full-Text Search Languages Scoring Query Processing Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search
Four Classes of Languages • Keyword search (INEX Content-Only Queries) – “book xml” • Tag + Keyword search – book: xml • Path Expression + Keyword search – /book[. /title about “xml db”] • XQuery + Complex full-text search – for $b in /book let score $s : = $b ftcontains “xml” && “db” distance 5 2 September 2005 VLDB Tutorial on XML Full-Text Search
Outline • Motivation • Full-Text Search Languages – – Simple Keyword Search Tags + Keyword Search Path Expressions + Keyword Search XQuery + Complex Full-Text Search • Scoring • Query Processing • Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search
![XRank [Guo et al. , SIGMOD 2003] <workshop date=” 28 July 2000”> <title> XML](https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-13.jpg "XRank [Guo et al. , SIGMOD 2003] <workshop date=” 28 July 2000”> <title> XML")
XRank [Guo et al. , SIGMOD 2003] XML and Information Retrieval: A SIGIR 2000 Workshop David Carmel, Yoelle Maarek, Aya Soffer XQL and Proximal Nodes Ricardo Baeza-Yates Gonzalo Navarro We consider the recently proposed language … Searching on structured text is becoming more important with XML … The XQL language … … … 2 September 2005 VLDB Tutorial on XML Full-Text Search …
![XRank [Guo et al. , SIGMOD 2003] <workshop date=” 28 July 2000”> <title> XML](https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-14.jpg "XRank [Guo et al. , SIGMOD 2003] <workshop date=” 28 July 2000”> <title> XML")
XRank [Guo et al. , SIGMOD 2003] XML and Information Retrieval: A SIGIR 2000 Workshop David Carmel, Yoelle Maarek, Aya Soffer XQL and Proximal Nodes Ricardo Baeza-Yates Gonzalo Navarro We consider the recently proposed language … Searching on structured text is becoming more important with XML … The XQL language … … … 2 September 2005 VLDB Tutorial on XML Full-Text Search …
![XIRQL [Fuhr & Grobjohann, SIGIR 2001] <workshop date=” 28 July 2000”> <title> XML and](https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-15.jpg "XIRQL [Fuhr & Grobjohann, SIGIR 2001] <workshop date=” 28 July 2000”> <title> XML and")
XIRQL [Fuhr & Grobjohann, SIGIR 2001] XML and Information Retrieval: A SIGIR 2000 Workshop David Carmel, Yoelle Maarek, Aya Soffer XQL and Proximal Nodes Ricardo Baeza-Yates Gonzalo Navarro Index Node We consider the recently proposed language … Searching on structured text is becoming more important with XML … The XQL language … … … 2 September 2005 VLDB Tutorial on XML Full-Text Search
Similar Notion of Results • Nearest Concept Queries – [Schmidt et al. , ICDE 2002] • XKSearch – [Xu & Papakonstantinou, SIGMOD 2005] 2 September 2005 VLDB Tutorial on XML Full-Text Search
Outline • Motivation • Full-Text Search Languages – – Simple Keyword Search Tags + Keyword Search Path Expressions + Keyword Search XQuery + Complex Full-Text Search • Scoring • Query Processing • Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search
![XSearch [Cohen et al. , VLDB 2003] <workshop date=” 28 July 2000”> <title> XML](https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-18.jpg "XSearch [Cohen et al. , VLDB 2003] <workshop date=” 28 July 2000”> <title> XML")
XSearch [Cohen et al. , VLDB 2003] XML and Information Retrieval: A SIGIR 2000 Workshop David Carmel, Yoelle Maarek, Aya Soffer XQL and Proximal Nodes Ricardo Baeza-Yates Gonzalo Navarro Not a We consider the recently proposed language … “meaningful” Searching on structured text is becoming more important with XML … result … XML Indexing … 2 September 2005 VLDB Tutorial on XML Full-Text Search
Outline • Motivation • Full-Text Search Languages – – Simple Keyword Search Tags + Keyword Search Path Expressions + Keyword Search XQuery + Complex Full-Text Search • Scoring • Query Processing • Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search
![XPath [W 3 C 2005] • fn: contains($e, string) returns true iff $e contains](https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-20.jpg "XPath [W 3 C 2005] • fn: contains($e, string) returns true iff $e contains")
XPath [W 3 C 2005] • fn: contains($e, string) returns true iff $e contains string //section[fn: contains(. /title, “XML Indexing”)] 2 September 2005 VLDB Tutorial on XML Full-Text Search
![XIRQL [Fuhr & Grobjohann, SIGIR 2001] • Weighted extension to XQL (precursor to XPath)](https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-21.jpg "XIRQL [Fuhr & Grobjohann, SIGIR 2001] • Weighted extension to XQL (precursor to XPath)")
XIRQL [Fuhr & Grobjohann, SIGIR 2001] • Weighted extension to XQL (precursor to XPath) //section[0. 6 ·. //* $cw$ “XQL” + 0. 4 ·. //section $cw$ “syntax”] 2 September 2005 VLDB Tutorial on XML Full-Text Search
![XXL [Theobald & Weikum, EDBT 2002] • Introduces similarity operator ~ Select Z From](https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-22.jpg "XXL [Theobald & Weikum, EDBT 2002] • Introduces similarity operator ~ Select Z From")
XXL [Theobald & Weikum, EDBT 2002] • Introduces similarity operator ~ Select Z From http: //www. myzoos. edu/zoos. html Where zoos. #. zoo As Z and Z. animals. (animal)? . specimen as A and A. species ~ “lion” and A. birthplace. #. country as B and A. region ~ B. content 2 September 2005 VLDB Tutorial on XML Full-Text Search
![NEXI [Trotman & Sigurbjornsson, INEX 2004] • Narrowed Extended XPath I • INEX Content-and-Structure](https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-23.jpg "NEXI [Trotman & Sigurbjornsson, INEX 2004] • Narrowed Extended XPath I • INEX Content-and-Structure")
NEXI [Trotman & Sigurbjornsson, INEX 2004] • Narrowed Extended XPath I • INEX Content-and-Structure (CAS) Queries //article[about(. //title, apple) and about(. //sec, computer)] 2 September 2005 VLDB Tutorial on XML Full-Text Search
Outline • Motivation • Full-Text Search Languages – – Simple Keyword Search Tags + Keyword Search Path Expressions + Keyword Search XQuery + Complex Full-Text Search • Scoring • Query Processing • Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search
![Schema-Free XQuery [Li, Yu, Jagadish, VLDB 2003] • Meaningful least common ancestor (mlcas) for](https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-25.jpg "Schema-Free XQuery [Li, Yu, Jagadish, VLDB 2003] • Meaningful least common ancestor (mlcas) for")
Schema-Free XQuery [Li, Yu, Jagadish, VLDB 2003] • Meaningful least common ancestor (mlcas) for $a in doc(“bib. xml”)//author $b in doc(“bib. xml”)//title $c in doc(“bib. xml”)//year where $a/text() = “Mary” and exists mlcas($a, $b, $c) return {$b, $c} 2 September 2005 VLDB Tutorial on XML Full-Text Search
![XQuery Full-Text [W 3 C 2005] • Two new XQuery constructs 1) FTContains. Expr](https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-26.jpg "XQuery Full-Text [W 3 C 2005] • Two new XQuery constructs 1) FTContains. Expr")
XQuery Full-Text [W 3 C 2005] • Two new XQuery constructs 1) FTContains. Expr • • Expresses “Boolean” full-text search predicates Seamlessly composes with other XQuery expressions 2) FTScore. Clause • • Extension to FLWOR expression Can score FTContains. Expr and other expressions 2 September 2005 VLDB Tutorial on XML Full-Text Search
FTContains. Expr //book ftcontains “Usability” && “testing” distance 5 //book[. /content ftcontains “Usability” with stems]/title //book ftcontains /article[author=“Dawkins”]/title 2 September 2005 VLDB Tutorial on XML Full-Text Search
![FTScore Clause In any FOR $v [SCORE $s]? IN [FUZZY] Expr order LET …](https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-28.jpg "FTScore Clause In any FOR $v [SCORE $s]? IN [FUZZY] Expr order LET …")
FTScore Clause In any FOR $v [SCORE $s]? IN [FUZZY] Expr order LET … WHERE … ORDER BY … RETURN Example FOR $b SCORE $s in /pub/book[. ftcontains “Usability” && “testing”] ORDER BY $s RETURN $b 2 September 2005 VLDB Tutorial on XML Full-Text Search
![FTScore Clause In any FOR $v [SCORE $s]? IN [FUZZY] Expr order LET …](https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-29.jpg "FTScore Clause In any FOR $v [SCORE $s]? IN [FUZZY] Expr order LET …")
FTScore Clause In any FOR $v [SCORE $s]? IN [FUZZY] Expr order LET … WHERE … ORDER BY … RETURN Example FOR $b SCORE $s in /pub/book[. ftcontains “Usability” && “testing” and. /price < 10. 00] ORDER BY $s RETURN $b 2 September 2005 VLDB Tutorial on XML Full-Text Search
![FTScore Clause In any FOR $v [SCORE $s]? IN [FUZZY] Expr order LET …](https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-30.jpg "FTScore Clause In any FOR $v [SCORE $s]? IN [FUZZY] Expr order LET …")
FTScore Clause In any FOR $v [SCORE $s]? IN [FUZZY] Expr order LET … WHERE … ORDER BY … RETURN Example FOR $b SCORE $s in FUZZY /pub/book[. ftcontains “Usability” && “testing”] ORDER BY $s RETURN $b 2 September 2005 VLDB Tutorial on XML Full-Text Search
XQuery Full-Text Evolution 2002 Quark Full-Text Language (Cornell) IBM, Microsoft, Oracle proposals Te. XQuery 2003 (Cornell, AT&T Labs) 2004 XQuery Full-Text 2005 XQuery Full-Text (Second Draft) 2 September 2005 VLDB Tutorial on XML Full-Text Search
Outline • • • Motivation Full-Text Search Languages Scoring Query Processing Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search
Full-Text Scoring • Score value should reflect relevance of answer to user query. Higher scores imply a higher degree of relevance. • Queries return document fragments. Granularity of returned results affects scoring. • For queries containing conditions on structure, structural conditions may affect scoring. • Existing proposals extend common scoring methods: probabilistic or vector-based similarity. 2 September 2005 VLDB Tutorial on XML Full-Text Search
Granularity of Results • Keyword queries – compute possibly different scores for LCAs. • Tag + Keyword queries – compute scores based on tags and keywords. • Path Expression + Keyword queries – compute scores based on paths and keywords. • XQuery + Complex full-text queries – compute scores for (newly constructed) XML fragments satisfying XQuery (structural, full-text and scalar conditions). 2 September 2005 VLDB Tutorial on XML Full-Text Search
Outline • Motivation • Full-Text Search Languages • Scoring – – Simple Keyword Search Tags + Keyword Search Path Expressions + Keyword Search XQuery + Complex Full-Text Search • Query Processing • Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search
Granularity of Results • Document as hierarchical structure of elements as opposed to flat document. – XXL [Theobald & Weikum, EDBT 2002] – XIRQL [Fuhr & Grobjohann, SIGIR 2001] – XRANK [Guo et al. , SIGMOD 2003] • Propagate keyword weights along document structure. 2 September 2005 VLDB Tutorial on XML Full-Text Search
XML Data Model Containment edge date 28 July … <editors> XML and … <proceedings> David Carmel … <paper> <title> XQL and … 2 September 2005 <author> Ricardo … <paper> … VLDB Tutorial on XML Full-Text Search … … Hyperlink edge </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="XXL [Theobald & Weikum, EDBT 2002] • Compute similar terms with relevance score r" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-38.jpg" alt="XXL [Theobald & Weikum, EDBT 2002] • Compute similar terms with relevance score r" />
XXL [Theobald & Weikum, EDBT 2002] • Compute similar terms with relevance score r 1 using an ontology. • Compute tf*idf of each term for a given element content with relevance score r 2. • Relevance of an element content for a term is r 1*r 2. • r 1 and r 2 are computed as a weighted distance in an ontology graph. • Probabilities of conjunctions multiplied (independence assumption) along elements of same path to compute path score. 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Probabilistic Scoring XIRQL [Fuhr & Grobjohann, SIGIR 2001] • Extension of XPath. • Weighting" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-39.jpg" alt="Probabilistic Scoring XIRQL [Fuhr & Grobjohann, SIGIR 2001] • Extension of XPath. • Weighting" />
Probabilistic Scoring XIRQL [Fuhr & Grobjohann, SIGIR 2001] • Extension of XPath. • Weighting and ranking: – weighting of query terms: • P(wsum((0. 6, a), (0. 4, b)) = 0. 6 · P(a)+0. 4 · P(b) – probabilistic interpretation of Boolean connectors: • P(a && b) = P(a) · P(b) 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="XIRQL Example • Query: – “Search for an artist named Ulbrich, living in Frankfurt," src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-40.jpg" alt="XIRQL Example • Query: – “Search for an artist named Ulbrich, living in Frankfurt," />
XIRQL Example • Query: – “Search for an artist named Ulbrich, living in Frankfurt, Germany about 100 years ago” • Data: – “Ernst Olbrich, Darmstadt, 1899” • Weights and ranking: – P(Olbrich p Ulbrich)=0. 8 (phonetic similarity) – P(1899 n 1903)=0. 9 (numeric similarity) – P(Darmstadt g Frankfurt)=0. 7 (geographic distance) 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Page. Rank [Brin & Page 1998] d/3 d/3 2 September 2005 : Hyperlink edge" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-41.jpg" alt="Page. Rank [Brin & Page 1998] d/3 d/3 2 September 2005 : Hyperlink edge" />
Page. Rank [Brin & Page 1998] d/3 d/3 2 September 2005 : Hyperlink edge d: Probability of following hyperlink w 1 -d: Probability of random jump VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Elem. Rank [Guo et al. SIGMOD 2003] d 1/3 : Hyperlink edge d 3" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-42.jpg" alt="Elem. Rank [Guo et al. SIGMOD 2003] d 1/3 : Hyperlink edge d 3" />
Elem. Rank [Guo et al. SIGMOD 2003] d 1/3 : Hyperlink edge d 3 d 1/3 : Containment edge w d 1/3 d 2/2 2 September 2005 d 2/2 d 1: Probability of following hyperlink d 2: Probability of visiting a subelement d 3: Probability of visiting parent 1 -d 2 -d 3: Probability of random jump VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Outline • Motivation • Full-Text Search Languages • Scoring – – Simple Keyword Search" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-43.jpg" alt="Outline • Motivation • Full-Text Search Languages • Scoring – – Simple Keyword Search" />
Outline • Motivation • Full-Text Search Languages • Scoring – – Simple Keyword Search Tags + Keyword Search Path Expressions + Keyword Search XQuery + Complex Full-Text Search • Query Processing • Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="XSearch [Cohen et al. , VLDB 2003] • tf*ilf to compute weight of keyword" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-44.jpg" alt="XSearch [Cohen et al. , VLDB 2003] • tf*ilf to compute weight of keyword" />
XSearch [Cohen et al. , VLDB 2003] • tf*ilf to compute weight of keyword for a leaf element. • A vector is associated with each non-leaf element. • sim(Q, N): sum of the cosine distances between the vectors associated with nodes in N and vectors associated with terms matched in Q. 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Outline • Motivation • Full-Text Search Languages • Scoring – – Simple Keyword Search" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-45.jpg" alt="Outline • Motivation • Full-Text Search Languages • Scoring – – Simple Keyword Search" />
Outline • Motivation • Full-Text Search Languages • Scoring – – Simple Keyword Search Tags + Keyword Search Path Expressions + Keyword Search XQuery + Complex Full-Text Search • Query Processing • Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Vector–based Scoring Juru. XML [Mass et al INEX 2002] • Transform query into (term," src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-46.jpg" alt="Vector–based Scoring Juru. XML [Mass et al INEX 2002] • Transform query into (term," />
Vector–based Scoring Juru. XML [Mass et al INEX 2002] • Transform query into (term, path) conditions: article/bm/bibl/bb[about(. , hypercube mesh torus nonnumerical database)] • (term, path)-pairs: hypercube, article/bm/bibl/bb mesh, article/bm/bibl/bb torus, article/bm/bibl/bb nonnumerical, article/bm/bibl/bb database, article/bm/bibl/bb • Modified cosine similarity as retrieval function for vague matching of path conditions. 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Juru. XML Vague Path Matching • Modified vector-based cosine similarity Example of length normalization:" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-47.jpg" alt="Juru. XML Vague Path Matching • Modified vector-based cosine similarity Example of length normalization:" />
Juru. XML Vague Path Matching • Modified vector-based cosine similarity Example of length normalization: cr (article/bibl, article/bm/bibl/bb) = 3/6 = 0. 5 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Query Relaxation on Structure • Schlieder, EDBT 2002 • Delobel & Rousset, 2002 •" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-48.jpg" alt="Query Relaxation on Structure • Schlieder, EDBT 2002 • Delobel & Rousset, 2002 •" />
Query Relaxation on Structure • Schlieder, EDBT 2002 • Delobel & Rousset, 2002 • Amer-Yahia et al, VLDB 2005 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="XML Query Relaxation [Amer-Yahia et al EDBT 2002] Flex. Path [Amer-Yahia et al SIGMOD" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-49.jpg" alt="XML Query Relaxation [Amer-Yahia et al EDBT 2002] Flex. Path [Amer-Yahia et al SIGMOD" />
XML Query Relaxation [Amer-Yahia et al EDBT 2002] Flex. Path [Amer-Yahia et al SIGMOD 2004] Query book • Tree pattern relaxations: – Leaf node deletion – Edge generalization – Subtree promotion Data 2 September 2005 author Dickens info edition (paperback) author Charles Dickens edition paperback book info author C. Dickens book edition? info edition paperback VLDB Tutorial on XML Full-Text Search author Dickens </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Adaptation of tf. idf to XML Whirlpool[Marian et al ICDE 2005] Document Collection (Information" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-50.jpg" alt="Adaptation of tf. idf to XML Whirlpool[Marian et al ICDE 2005] Document Collection (Information" />
Adaptation of tf. idf to XML Whirlpool[Marian et al ICDE 2005] Document Collection (Information Retrieval) XML Document XML Node (result is a subtree rooted at a returned node with a given tag and satisfying structural predicates in the query) Keyword(s) Tree Pattern idf (inverse document frequency) is a function of the fraction of documents that contain the keyword(s) idf is a function of the fraction of returned nodes that match the query tree pattern tf (term frequency) is a function of the tf is a function of the number of ways number of occurrences of the keyword in the query tree pattern matches the document returned node 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="A Family of XML Scoring Methods [Amer-Yahia et al VLDB 2005] book Query •" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-51.jpg" alt="A Family of XML Scoring Methods [Amer-Yahia et al VLDB 2005] book Query •" />
A Family of XML Scoring Methods [Amer-Yahia et al VLDB 2005] book Query • Twig scoring – High quality – Expensive computation info • Path scoring • Binary scoring edition (paperback) author (Dickens) – Low quality – Fast computation book info edition (paperback) author (Dickens) 2 September 2005 book + book info edition (paperback) book + book author info edition (Dickens) (paperback) author (Dickens) VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Outline • Motivation • Full-Text Search Languages • Scoring – – Simple Keyword Search" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-52.jpg" alt="Outline • Motivation • Full-Text Search Languages • Scoring – – Simple Keyword Search" />
Outline • Motivation • Full-Text Search Languages • Scoring – – Simple Keyword Search Tags + Keyword Search Path Expressions + Keyword Search XQuery + Complex Full-Text Search • Query Processing • Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="XIRQL + Relaxation • XIRQL proposes vague predicates but it is not clear how" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-53.jpg" alt="XIRQL + Relaxation • XIRQL proposes vague predicates but it is not clear how" />
XIRQL + Relaxation • XIRQL proposes vague predicates but it is not clear how to combine it with all of XQuery. • Open issue as how to relax all of XQuery including structured and scalar predicates. 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Outline • • • Motivation Full-Text Search Languages Scoring Query Processing Open Issues 2" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-54.jpg" alt="Outline • • • Motivation Full-Text Search Languages Scoring Query Processing Open Issues 2" />
Outline • • • Motivation Full-Text Search Languages Scoring Query Processing Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Outline • • Motivation Full-Text Search Languages Scoring Query Processing – – Simple Keyword" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-55.jpg" alt="Outline • • Motivation Full-Text Search Languages Scoring Query Processing – – Simple Keyword" />
Outline • • Motivation Full-Text Search Languages Scoring Query Processing – – Simple Keyword Search Tags + Keyword Search Path Expressions + Keyword Search XQuery + Complex Full-Text Search • Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Main Issue • Given: Query keywords • Compute: Least Common Ancestors (LCAs) that contain" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-56.jpg" alt="Main Issue • Given: Query keywords • Compute: Least Common Ancestors (LCAs) that contain" />
Main Issue • Given: Query keywords • Compute: Least Common Ancestors (LCAs) that contain query keywords, in ranked order 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Naïve Method <workshop> date 2 <title> 3 Naïve inverted lists: 1 <editors> 4 <proceedings>" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-57.jpg" alt="Naïve Method <workshop> date 2 <title> 3 Naïve inverted lists: 1 <editors> 4 <proceedings>" />
Naïve Method <workshop> date 2 <title> 3 Naïve inverted lists: 1 <editors> 4 <proceedings> 5 Ricardo 1 ; 5 ; 6 ; 8 n. XQL 1; 5; 6; 7 n 28 July … XML and … David Carmel … <paper> <title> 7 <author> XQL and … 8 Ricardo … 6 <paper> … … … Problems: 1. Space Overhead 2. Spurious Results Main issue: Decouples representation of ancestors and descendants 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Dewey Encoding of IDs [1850 s] <workshop> date 0. 0 28 July … <title>" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-58.jpg" alt="Dewey Encoding of IDs [1850 s] <workshop> date 0. 0 28 July … <title>" />
Dewey Encoding of IDs [1850 s] <workshop> date 0. 0 28 July … <title> 0. 1 XML and … 0 <editors> 0. 3. 0. 0 XQL and … 2 September 2005 <proceedings> 0. 3 David Carmel … <paper> <title> 0. 2 <author> 0. 3. 0. 1 <paper> … Ricardo … VLDB Tutorial on XML Full-Text Search 0. 3. 1 … … </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="XQL Po sit e or Sc De we y Id ion L ist XRank:" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-59.jpg" alt="XQL Po sit e or Sc De we y Id ion L ist XRank:" />
XQL Po sit e or Sc De we y Id ion L ist XRank: Dewey Inverted List (DIL) 5. 0. 3. 0. 0 85 32 8. 0. 3. 8. 3 38 89 91 … … … Ricardo 5. 0. 3. 0. 1 82 38 8. 2. 1. 4. 2 99 52 … … … Sorted by Dewey Id Store IDs of elements that directly contain keyword - Avoids space overhead 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="DIL: Query Processing • Merge query keyword inverted lists in Dewey ID Order –" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-60.jpg" alt="DIL: Query Processing • Merge query keyword inverted lists in Dewey ID Order –" />
DIL: Query Processing • Merge query keyword inverted lists in Dewey ID Order – Entries with common prefixes are processed together • Compute Longest Common Prefix of Dewey IDs during the merge – Longest common prefix ensures most specific results – Also suppresses spurious results • Keep top-m results seen so far in output heap – Calculate rank using two-dimensional proximity metric – Output contents of output heap after scanning inverted lists • Algorithm works in a single scan over inverted lists 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="XRank: Ranked Dewey Inverted List (RDIL) B+-tree On Dewey Id XQL Inverted List …" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-61.jpg" alt="XRank: Ranked Dewey Inverted List (RDIL) B+-tree On Dewey Id XQL Inverted List …" />
XRank: Ranked Dewey Inverted List (RDIL) B+-tree On Dewey Id XQL Inverted List … Sorted by Score …(other keywords) 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="RDIL: Algorithm • An element may be ranked highly in one list and low" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-62.jpg" alt="RDIL: Algorithm • An element may be ranked highly in one list and low" />
RDIL: Algorithm • An element may be ranked highly in one list and low in another list – B+-tree helps search for low ranked element • When to stop scanning inverted lists? – Based on Threshold Algorithm [Fagin et al. , 2002], which periodically calculates a threshold – Can stop if we have sufficient results above threshold – Extension to most specific results 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="RDIL: Query Processing P P Output Heap Temp Heap B+-tree on Dewey Id Ricardo" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-63.jpg" alt="RDIL: Query Processing P P Output Heap Temp Heap B+-tree on Dewey Id Ricardo" />
RDIL: Query Processing P P Output Heap Temp Heap B+-tree on Dewey Id Ricardo P: 9. 0. 4. 2. 0 Rank(9. 0. 4) XQL Inverted List threshold = Score(P)+Score(R) threshold = Score(P)+Max-Score R 9. 0. 4. 1. 2 8. 2. 1. 4. 2 9. 0. 4. 1. 2 9. 0. 5. 6 10. 8. 3 B+-tree on Dewey Id 9. 0. 4. 2. 0 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="ID Order vs. Rank Order • Approaches that combine benefits • Long ID inverted" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-64.jpg" alt="ID Order vs. Rank Order • Approaches that combine benefits • Long ID inverted" />
ID Order vs. Rank Order • Approaches that combine benefits • Long ID inverted list, short score inverted list – HDIL (Guo et al. , SIGMOD 2003) • Chunk inverted list based on score, organize by ID within chunk – Flex. Path (Amer-Yahia et al. , SIGMOD 2004) – SVR (Guo et al. , ICDE 2005) 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Outline • • Motivation Full-Text Search Languages Scoring Query Processing – – Simple Keyword" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-65.jpg" alt="Outline • • Motivation Full-Text Search Languages Scoring Query Processing – – Simple Keyword" />
Outline • • Motivation Full-Text Search Languages Scoring Query Processing – – Simple Keyword Search Tags + Keyword Search Path Expressions + Keyword Search XQuery + Complex Full-Text Search • Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="XSearch Technique • Given: An interconnection relationship R between nodes (semantic relationship) – R" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-66.jpg" alt="XSearch Technique • Given: An interconnection relationship R between nodes (semantic relationship) – R" />
XSearch Technique • Given: An interconnection relationship R between nodes (semantic relationship) – R is reflexive and symmetric • Node interconnection index – Given two nodes n and n’ in a document d, find if (n, n’) are in R* • Use dynamic programming to compute closure – Online vs. offline 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Outline • • Motivation Full-Text Search Languages Scoring Query Processing – – Simple Keyword" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-67.jpg" alt="Outline • • Motivation Full-Text Search Languages Scoring Query Processing – – Simple Keyword" />
Outline • • Motivation Full-Text Search Languages Scoring Query Processing – – Simple Keyword Search Tags + Keyword Search Path Expressions + Keyword Search XQuery + Complex Full-Text Search • Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="XXL Indexing • Element Path Index (EPI) – Evaluates simple path expressions • Element" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-68.jpg" alt="XXL Indexing • Element Path Index (EPI) – Evaluates simple path expressions • Element" />
XXL Indexing • Element Path Index (EPI) – Evaluates simple path expressions • Element Content Index (ECI) – Traditional inverted list (but replicates nested elements) • Ontology Index (OI) – Lookup similar concepts (for evaluating ~e) – Returned in ranked order 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Do cu El me em nt El ent ID em ID e Pr nt" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-69.jpg" alt="Do cu El me em nt El ent ID em ID e Pr nt" />
Do cu El me em nt El ent ID em ID e Pr nt T ob ab ag ili El em ty en t. T Pr ob ag ab ili El em ty en t. T Pr ag ob ab ili ty Myaeng et al. [SIGIR 1994] XQL 5 85 act 0. 3 play 0. 2 plays 0. 1 … … 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="book 2 info author 4 edition title 5 3 Do 1 cu St me" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-70.jpg" alt="book 2 info author 4 edition title 5 3 Do 1 cu St me" />
book 2 info author 4 edition title 5 3 Do 1 cu St me art nt En ID ID d. I De D In pth de Sc x ID or e Integrating Structure and IL [Kaushik et al. , SIGMOD 2004] XQL 5 85 99 3 5 0. 9 … … B+ Tree 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Outline • • Motivation Full-Text Search Languages Scoring Query Processing – – Simple Keyword" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-71.jpg" alt="Outline • • Motivation Full-Text Search Languages Scoring Query Processing – – Simple Keyword" />
Outline • • Motivation Full-Text Search Languages Scoring Query Processing – – Simple Keyword Search Tags + Keyword Search Path Expressions + Keyword Search XQuery + Complex Full-Text Search • Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Scoring Functions Critical for Top-k Query Processing • Top-k answer quality depends on scoring" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-72.jpg" alt="Scoring Functions Critical for Top-k Query Processing • Top-k answer quality depends on scoring" />
Scoring Functions Critical for Top-k Query Processing • Top-k answer quality depends on scoring function. • Efficient top-k query processing requires scoring function to be: – Monotone. – Fast to compute. 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Structural Join Relaxation //book[. /info[. /author ftcontains “Dickens”] [. /edition ftcontains “paperback”]] contains(edition, ”paperback”)" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-73.jpg" alt="Structural Join Relaxation //book[. /info[. /author ftcontains “Dickens”] [. /edition ftcontains “paperback”]] contains(edition, ”paperback”)" />
Structural Join Relaxation //book[. /info[. /author ftcontains “Dickens”] [. /edition ftcontains “paperback”]] contains(edition, ”paperback”) paperback contains(author, ”Dickens”) Dickens pc(info, edition) or ad(book, edition) pc(info, edition) edition pc(info, author) author pc(book, info) book info 2 September 2005 pc(book, info) or ad(book, info) book info VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Quark/Gala. Tex Architecture <xml> <doc> Text </doc> </xml Preprocessing & Inverted Lists Generation s" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-74.jpg" alt="Quark/Gala. Tex Architecture <xml> <doc> Text </doc> </xml Preprocessing & Inverted Lists Generation s" />
Quark/Gala. Tex Architecture <xml> <doc> Text </doc> </xml Preprocessing & Inverted Lists Generation s n o PI . xml po ns o iti 4 Full-Text Primitives (FTWord, FTWindow, FTTimes etc. ) A inverted lists Quark/Galax XQuery Engine Full-Text Query 2 September 2005 XQFT Parser Equivalent XQuery VLDB Tutorial on XML Full-Text Search evaluation <doc> Text </doc> . xml </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Outline • • • Motivation Full-Text Search Languages Scoring Query Processing Open Issues 2" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-75.jpg" alt="Outline • • • Motivation Full-Text Search Languages Scoring Query Processing Open Issues 2" />
Outline • • • Motivation Full-Text Search Languages Scoring Query Processing Open Issues 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="System Architecture Integration Layer XQuery Engine 2 September 2005 IR Engine VLDB Tutorial on" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-76.jpg" alt="System Architecture Integration Layer XQuery Engine 2 September 2005 IR Engine VLDB Tutorial on" />
System Architecture Integration Layer XQuery Engine 2 September 2005 IR Engine VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="System Architecture XQuery + IR Engine Quark/Gala. Tex use this architecture 2 September 2005" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-77.jpg" alt="System Architecture XQuery + IR Engine Quark/Gala. Tex use this architecture 2 September 2005" />
System Architecture XQuery + IR Engine Quark/Gala. Tex use this architecture 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Structural Relaxation FOR $b SCORE $s in FUZZY /pub/book[. ftcontains “Usability” with stems] ORDER" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-78.jpg" alt="Structural Relaxation FOR $b SCORE $s in FUZZY /pub/book[. ftcontains “Usability” with stems] ORDER" />
Structural Relaxation FOR $b SCORE $s in FUZZY /pub/book[. ftcontains “Usability” with stems] ORDER BY $s RETURN $b 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Search Over Views Data Source 1 <books> <book> … </book> … </books> Data Source" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-79.jpg" alt="Search Over Views Data Source 1 <books> <book> … </book> … </books> Data Source" />
Search Over Views Data Source 1 <books> <book> … </book> … </books> Data Source 2 <reviews> <review> … </review> … </reviews> <book> <reviews> … </reviews> Integrated </book> View … 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Other Open Issues • Extensive experimental evaluation of scoring functions and ranking algorithms for" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-80.jpg" alt="Other Open Issues • Extensive experimental evaluation of scoring functions and ranking algorithms for" />
Other Open Issues • Extensive experimental evaluation of scoring functions and ranking algorithms for XML (INEX). • Joint scoring on full-text and scalar predicates. • Score-aware algebra for XML for the joint optimization of queries on both structure and text. 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Backup Slides 2 September 2005 VLDB Tutorial on XML Full-Text Search " src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-81.jpg" alt="Backup Slides 2 September 2005 VLDB Tutorial on XML Full-Text Search " />
Backup Slides 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Why not use SQL/MM (or variant)? • Key difference: No strict demarcation between structured" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-82.jpg" alt="Why not use SQL/MM (or variant)? • Key difference: No strict demarcation between structured" />
Why not use SQL/MM (or variant)? • Key difference: No strict demarcation between structured and text data in XML – Can issue structured and text queries over same data • Find books with year > 1995 • Find books containing keyword “ 1998” – Can embed structured queries in text queries • Find books that contain the keywords that occur in the title of Richard Dawkins’ books • Other important differences – XML/XQuery data model – Composability of full-text primitives 2 September 2005 VLDB Tutorial on XML Full-Text Search </p>
</div>
<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="Scoring Function (monotonicity) book • Required properties: book – Exact matches should be info" src="https://present5.com/presentation/19bbd84813175ee7a99d5280fa8c984b/image-83.jpg" alt="Scoring Function (monotonicity) book • Required properties: book – Exact matches should be info" />
Scoring Function (monotonicity) book • Required properties: book – Exact matches should be info edition info scored higher than relaxed info edition info (paperback) matches (idf) (paperback) author – Returned elements with author title (Dickens) several matches should be (Dickens) (Great ranked higher than those with Expectations) fewer matches (tf) • How to combine tf and idf? – tf. idf, as used by IR, violates above properties – Ranking based on idf, then breaking ties using tf satisfies the properties 2 September 2005 (a) (b) score(a) >= score(b) <= VLDB Tutorial on XML Full-Text Search </p>
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<div style="width: auto;" class="description columns twelve"><p><img class="imgdescription" title="" src="" alt="" />
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