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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

Keyword Searching and Browsing in Databases using BANKS

Seoyoung Ahn

Mar 3, 2005

The University of Texas at Arlington

outline
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

introduction
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

introduction cond

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

introduction cond5
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

outline6
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

database and query model
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

database and query model8
Database and Query Model
  • The Schema

Keyword Searching and Browsing in Databases using BANKS

database and query model9
Database and Query Model
  • A Fragment of the Database

Keyword Searching and Browsing in Databases using BANKS

database and query model10
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

database and query model11
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

database and query model12
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

database and query model13
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

database and query model14
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

database and query model15
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

database and query model16
Database and Query Model
  • Result of query “sudarshan soumen”

Keyword Searching and Browsing in Databases using BANKS

outline17
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

searching for the best answers
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

searching for the best answers19
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

outline20
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

browsing
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

browsing22
Browsing
  • Data browsing

Keyword Searching and Browsing in Databases using BANKS

browsing23
Browsing
  • Schema browsing

Keyword Searching and Browsing in Databases using BANKS

outline24
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

error scores vs parameter choices
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

outline26
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

conclusion
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