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Keyword Searching and Browsing in Databases using BANKS

Keyword Searching and Browsing in Databases using BANKS. Seoyoung Ahn Mar 3, 2005 The University of Texas at Arlington. Outline. Introduction Database and Query Model Searching for the best answers Browsing features of BANKS Experiment Conclusion. Introduction.

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Keyword Searching and Browsing in Databases using BANKS

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  1. Keyword Searching and Browsing in Databases using BANKS Seoyoung Ahn Mar 3, 2005 The University of Texas at Arlington

  2. Outline • Introduction • Database and Query Model • Searching for the best answers • Browsing features of BANKS • Experiment • Conclusion Keyword Searching and Browsing in Databases using BANKS

  3. Introduction • Search engines on Web have popularized an unstructured querying and browsing • Simple and user-friendly • Users just type in keywords and follow hyperlink • Relational databases are commonly searched using structured query language • Users need to know the schema • Keyword searching techniques cannot be used on data stored in databases • It often splits across the tables/tuples due to normalization Keyword Searching and Browsing in Databases using BANKS

  4. BANKS system Introduction(cond..) • BANKS (Browsing And Keyword Searching) • a system which enables keyword-based search on relational databases, together with data and schema browsing HTTP JDBC User Database Keyword Searching and Browsing in Databases using BANKS

  5. Introduction(cond..) • BANKS (Browsing And Keyword Searching) • a framework for keyword querying of relational database • a novel and efficient heuristic algorithm for executing keyword queries • key features of BANKS system Keyword Searching and Browsing in Databases using BANKS

  6. Outline • Introduction • Database and Query Model • Informal Model • Formal Model • Query and Answer Model • Searching for the best answers • Browsing features of BANKS • Experiment • Conclusion Keyword Searching and Browsing in Databases using BANKS

  7. Database and Query Model • Informal Model • Model Description directed graph  database node in the graph each tuple in db   directed edge fk-pk-Link Keyword Searching and Browsing in Databases using BANKS

  8. Database and Query Model • The Schema Keyword Searching and Browsing in Databases using BANKS

  9. Database and Query Model • A Fragment of the Database Keyword Searching and Browsing in Databases using BANKS

  10. Database and Query Model • Informal Model(cond.) • An answer to a query should be a subgraph connecting nodes matching the keywords. • The importance of a link depends upon the type of the link i.e. what relations it connects and on its semantics • Ignoring directionality would cause problems because of “hubs” which are connected to a large numbers of nodes. Keyword Searching and Browsing in Databases using BANKS

  11. Database and Query Model • Formal Database Model • Nodes and edges • Node Weight : N(u) • Depends on the prestige • Set the node prestige = the indegree of the node • Nodes that have multiple pointers to them get a higher prestige • Node score N = root node weight + ∑ leaf node weight Keyword Searching and Browsing in Databases using BANKS

  12. Database and Query Model • Formal Database Model (Cond.) • Edge Weights • Some pupluar tuples can be connected many other tuples  Edge with forward and backward edge weights • Weight of a forward link = the strength of the proximity relationship between two tuples (set to 1 by default) • Weight of a backward link = indegree of edges pointing to the node • Total edge weight = ∑ edge weights • Edge score E = 1 / Total edge weight Keyword Searching and Browsing in Databases using BANKS

  13. Database and Query Model • Formal Database Model (Cond.) • Overall relevance score = Node weights + Edge Weight • Normalize in the range [0,1] • Combine using weighting factor  • Additive: (1- ) E + N; • multiplicative: E * N  Keyword Searching and Browsing in Databases using BANKS

  14. Database and Query Model • Query and Answer Model • Query • A set of keywords e.g.{k1,k2,…kn} • A set of nodes Si = {S1,S2,…Sn} • Locate nodes matching search terms t1,t2,…tn • Answer Model • A rooted directed tree connecting keyword nodes • Relevance score of an answer tree • Relevance scores of it nodes and its edge weight Keyword Searching and Browsing in Databases using BANKS

  15. Database and Query Model • Answer Model • A rooted directed tree connecting keyword nodes • Multiple answers • Ranked by proximity + prestige • Proximity  edges weights • Prestige  indegree of nodes • Relevance score of an answer tree • Relevance scores of it nodes and its edge weight Keyword Searching and Browsing in Databases using BANKS

  16. Database and Query Model • Result of query “sudarshan soumen” Keyword Searching and Browsing in Databases using BANKS

  17. Outline • Introduction • Database and Query Model • Searching for the best answers • Backward expanding search algorithm • Browsing features of BANKS • Experiment • Conclusion Keyword Searching and Browsing in Databases using BANKS

  18. Searching for the best answers • Backward expanding search algorithm • Offers a heuristic solution for incrementally computing query results. • Assume that the graph fits in memory • Start at leaf nodes each containing a query keyword • Run concurrent single source shortest path algorithm from each such node • Traverses the graph edges backwards • Confluence of backward paths identify answer tree roots • Output a node whenever it is on the intersection of the sets of nodes reached from each keyword • Answer trees may not be generated in relevance order • Insert answers to a small buffer (heap) • Output highest ranked answer from buffer to user when buffer is full Keyword Searching and Browsing in Databases using BANKS

  19. Searching for the best answers • Model (Query : Charuta Sudarshan Roy ) BANKS: Keyword search… paper writes Charuta S. Sudarshan Prasan Roy author Keyword Searching and Browsing in Databases using BANKS

  20. Outline • Introduction • Database and Query Model • Searching for the best answers • Browsing features of BANKS • Experiment • Conclusion Keyword Searching and Browsing in Databases using BANKS

  21. Browsing • BANKS system provides • A rich interface to browse data stored in a relational database • Automatically generates browsable views of database relations and query results • Schema browsing and data browsing • A hyperlink to the referenced tuple • Templates for several predefined ways of displaying data Keyword Searching and Browsing in Databases using BANKS

  22. Browsing • Data browsing Keyword Searching and Browsing in Databases using BANKS

  23. Browsing • Schema browsing Keyword Searching and Browsing in Databases using BANKS

  24. Outline • Introduction • Database and Query Model • Searching for the best answers • Browsing features of BANKS • Experiment • Conclusion Keyword Searching and Browsing in Databases using BANKS

  25. Error scores vs parameter choices • The rankings are relatively stable across different choices of parameter values •  = 0.2 coupled with log scaling of edges weights does best Keyword Searching and Browsing in Databases using BANKS

  26. Outline • Introduction • Database and Query Model • Searching for the best answers • Browsing features of BANKS • Experiment • Conclusion Keyword Searching and Browsing in Databases using BANKS

  27. Conclusion • BANKS system • provides an integrated browsing and keyword querying system for relational databases • allows users with no knowledge of database systems or schema to query and browse relational database with ease Keyword Searching and Browsing in Databases using BANKS

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