Flexible Querying of XML Documents

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Flexible Querying of XML Documents

• Krishnaprasad Thirunarayan and Trivikram Immaneni
• Department of Computer Science and Engineering
• Wright State University
• Dayton, OH-45435, USA

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Talk Outline

• Goal (What?)
• Background and Motivation (Why?)
• Query Language and Examples (What?)
• Implementation Details (How?)
• Evaluation and Applications (Why?)
• Conclusions

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Goal
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• Develop a keyword-based XML Query Language and
  its Semantics that is
• flexible and sufficiently expressive
• easy to use (for query formulation)
• Implement, reusing mature software components,
  for efficient indexing and search

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Background and Motivation
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XML vs Text Documents

• DATA Exploit metadata/markup and aggregation
  structure implicit in XML documents
• For expressiveness and precision
• QUERY Obtain progressively improved extractions
  using convenient keyword-based queries in
  contrast with accurate extractions using complex
  XML-based queries

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Relationship to Other Work

• Extends XSEarch (Cohen et al)
• Expressive power Incorporates attributes and
  their values
• Equivalence (E.g., RDF)
• ltT A"s"/gt
• vs
• ltTgt ltAgt s lt/Agt lt/Tgt

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• Invariance under Refinement
• ltTgt ltAgt word_1 and word_2 lt/Agt lt/Tgt
• vs
• ltTgt ltAgt
• ltBgt word_1 lt/Bgt
• and
• ltCgt word_2 lt/Cgt
• lt/Agt lt/Tgt

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Coherence

• Interconnectedness Infer related pieces of
  information using aggregation implicit in XML
• Cohen et al Name equivalence
• XSEarch
• Li et al Structural equivalence
• Scheme-free XML
• Guo et al Completeness
• XRANK

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• Information Retrieval
• Explore robust relevance ranking strategy to deal
  with high recall
• Variation on TFIDF
• Naïve implementation computationally prohibitive
• Extension beyond type-delimited-document
  unclear

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Query Language and Examples (What?)
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Query Syntax

• Entity-Attribute-Keyword
• Search Terms
• eak
• ea, ak, ek
• e, a, k
• Signed/optional Search Terms
• eak vs eak

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Single Search Term Satisfaction

• eak
• The search term eak is satisfied by a tree
  containing a subtree with the top element e that
  is associated with the attribute a with value
  containing k, or a subelement a with descendant
  text node containing k.

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Example (Mondial)

• ltcountry id"f0_149" name"Austria"
  capital"f0_1467" population"8023244"
• datacode"AU" total_area"83850"
  population_growth"0.41"
• infant_mortality"6.2" ...
  government"federal republic" ...gt ...
• lt/countrygt
• nameVienna is satisfied by
• ltprovince id"f0_17447" name"Vienna" ...gt
• ltcity id"f0_1467" country"f0_149"
  province"f0_17447" ...gt
• ltnamegtViennalt/namegt ltpopulation
  year"94"gt1583000lt/populationgt lt/citygt
• lt/provincegt ...
• nameVienna is satisfied by a part of it
• ltnamegtViennalt/namegt.

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Example (Heterogeneity)

• ltauthorgtltnamegtAdam Dinglelt/namegtlt/authorgt
• ltauthor name"A. Dingle" gtlt/authorgt
• ltarticle id"3"gt
• _at_inproceedingsIMN97,
• author"Adam Dingle and Ed MacNair and
  Thao Nguyen",
• lt/articlegt
• authornameDingle misses the last one.

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Query Answer Candidate

• Query Answer Candidate for the query
  Q(t_1,t_2,...,t_m), is a
• Most preferred satisfying collection of trees
  (P_1,P_2,...,P_m)
• Precise smallest enclosing
• Adequate optional search terms satisfied as
  much as possible

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Query Answer

• Query Answer for the query Q(t_1,t_2,...,t_m), is
  a
• Query Answer Candidate (P_1,P_2,...,P_m) in
  which
• Trees P_is are Interconnected
• Specifies trees related to the same real-world
  entity

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Interconnectedness (Cohen et al)

• Two subtrees T_a and T_b are said to be
  interconnected if the path from their roots to
  the lowest common ancestor does not contain two
  distinct nodes with the same element, or the only
  distinct nodes with the same element are these
  roots.

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Interconnectedness (Li et al)

• Two subtrees T_a and T_b are said to be
  interconnected, if the path from T_a's root to
  their lowest common ancestor in the tree does not
  contain another node that is the lowest common
  ancestor of T_a and a distinct subtree T_b ,
  where T_b' has the same root element label as T_b.

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Interconnectedness (Two Approaches)
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Implementation Details (How?)
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Tools Used

• Apache Lucene 2.0 APIs in Java
• A high-performance, text search engine library
  with smart indexing strategies.
• Further tuned for memory-centric operation in
  contrast with disk-centric defaults
• SAXParser APIs

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Mapping to Lucene

• XML documents to Lucene documents for indexing
• XML keyword-based queries to Lucene queries for
  searching
• ENCODING
• XML fragment of an XML document is referred to
  internally using the filename and the XPath (of
  the XML fragment's root from the XML document
  root),

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Evaluation and Application (Why?)
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Experiments

• DATASETs Sigmod, Mondial, and DBLP.
• PLATFORMS
• For Sigmod and Mondial datasets HP xw9300
  Workstation with 2 GHz AMD Opteron dual-core
  processor (270), 4 GB of main memory, and 250 GB
  7200 rpm hard drive, running 32-bit Windows XP.
  
• (java -Xms750M -Xmx1500M).
• For DBLP dataset SUN Ultra-40 Workstation with
  2.4 GHz dual AMD Opteron dual-core processor
  (280), 8GB of main memory, and 250GB 7500 rpm
  hard drive, running 64-bit Solaris 10.
• (java -Xms1000M -Xmx3600M).

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Dataset Sizes
DATASET SIZE
Sigmod 468 KB
Mondial 1743 KB
DBLP 337 MB
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Dataset Indexing via Lucene
DATASET INDEXING TIME INDEX SIZE
Sigmod 32 sec 6 MB
Mondial 180 sec 16 MB
DBLP 36 hrs 4 GB
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Query Answer Computation Time vs Display Time
DATASET SIMPLE QUERY COMPLEX QUERY
Sigmod 35 ms / 1 sec 400 ms / 3 min
Mondial 25 ms / 350 ms 1 sec / 2 min
DBLP 335 ms / 1 sec ---
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More Subtle Example

• In Extended Paper
• A Coherent Keyword-Based XML Query Language

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Pubs.xml

• ltpublicationsgt
• - ltbookgt
•   lttitlegtModern Information Retrievallt/titlegt
•   ltauthorgtRicardo Baeza-Yateslt/authorgt  
  ltauthorgtBerthier Ribeiro-Netolt/authorgt
• - ltchaptergt
•   lttitlegtDigital Librarieslt/titlegt
•   ltauthorgtEdward A. Foxlt/authorgt  
  ltauthorgtOhm Sornillt/authorgt
•   lt/chaptergt
•   lt/bookgt
• - ltarticlegt
•   lttitlegtThe Anatomy of a Large-Scale
  Hypertextual Web Search Enginelt/titlegt
•   ltauthorgtSergey Brinlt/authorgt  
  ltauthorgtLawrence Pagelt/authorgt
•   lt/articlegt
• - ltarticlegt
•   lttitlegtAn Algorithm for Suffix
  Strippinglt/titlegt
•   ltauthorgtM.F.Porterlt/authorgt
•   lt/articlegt
• - ltarticlegt
• lttitlegtIndexing by Latent Semantic
  Analysislt/titlegt  

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Characteristics of Pubs.xml

• Total number of authors 7
• Total number of titles 5
• Title Distribution
• 1 book (with 1 chapter) 3 articles
• Author Distribution
• 2 ( 2 ) 2 1 0

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Queries to Pubs.xml (Answer counts)

• Arbitrary mix and match of authors and titles 7
  5 35
• author, title (8 hits)
• author, title (7 hits)
• author, title, author (4 hits)

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Completeness ( pWord, qWord) (Guo et al)
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Conclusions
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• Developed declarative semantics for keyword-based
  XML Query language with an effective query
  answering algorithm
• Developed a notion of interconnectedness that
  provides coherent answers
• Implemented using Lucene 2.0 APIs
• Indexing Time and Space Intensive
• But
• Query Answering Quick

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• THANK YOU!