Keyword Searching and Browsing in Databases using BANKS

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