TOPIC CENTRIC QUERY ROUTING

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TOPIC CENTRIC QUERY ROUTING

• Research Methods (CS689)
• 11/21/00

By Anupam Khanal
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• Introduction
• What is query routing?
• Searching online can be both rewarding and
  frustrating.
• General search engines such as Yahoo, Lycos
  return many
• irrelevant information to users query.
• In such context, query routing attempts
  dynamically route
• each users query to the appropriate
  specialized search.

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Problem Description

• There are many general search engines such as
  Yahoo,
• Lycos, Alta Vista etc.
• There are also many topic specific search
  engines such as VaccationSpot.com,
  KidsHealth.com etc.
• However, many casual users are not familiar
  with all these topic specific search engines.
• In such context, topic centric query expansion
  is important.

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Why Topic Centric Query Routing

• It is of utmost importance to analyze other query
  routing systems as well before we discuss the
  importance of Topic
• Centric routing.
• Manual Query Routing Services
• - provide the categorized list of specialized
  search engine - users have to choose the
  search engines
• - although keyword search interface is
  provided the terms that can be accepted
  as the keywords are limited.
• Query Routing based on Centroids
• - consist centroids which are summaries
  of databases
• - these summaries consists a complete
  list of terms and frequencies of the
  databases.

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• - search engine is located by dividing
  which databases are relevant to a user query by
  comparing the query with each centroid.
• - this technique cannot be applied to
  most of the topic specific search engines
  provided on the Web because of the restricted
  access to their internal database.
• Query Routing Without Centroids
• - Instead of centroids this systems generate
  a short text to explain the centroids of
  databases.
• - if the search keywords are contained is
  such text then only the search engine will
  be located.

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Research Objective

• In such context, Topic Centric Query Routing is
• appropriate as it uses the routing model to
  expand
• the query.
• The general framework of the query routing model
  is as
• follows
• Getting relevant terms from the Web
• - routing model does not use any special
  dictionaries, but it uses the Web as the
  source of relevant terms.
• - finds the Web documents relevant to
  the user query
• dynamically by submitting that query
  to a general search engine.
• - the relevant terms are extracted from
  those documents.

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• Co-occurrence based evaluation of term
  relevance.
• - the mutual relevance of terms is evaluated
  on the basis
• of their co-occurrences in the documents.
• - the co-occurrences of the search keywords
  are counted
• in all the documents retrieved by the
  general search engine.
• - the routing model list all the distinct
  terms contained in
• all documents and counts for each term the
  number of
• documents that contain both the search key
  word and that
• term.
• Using a pseudo-feedback technique
• - it is difficult to determine the term
  relevance from only the
• results of a single document search on the
  general search
• engine.

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• -even relevant terms often have few
  co-occurrences in
• the selected documents of the first search.
• in such context, query routing model re-evaluates
• such low co-occurrences terms selecting terms to
  be
• re-evaluated from the first search results,
  formulating
• new queries by adding the selected terms to the
  original
• query and performing the co-occurrence based
  evaluation
• for each formulated query.

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Figure 4 Query expansion procedure.
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6. Clustering all terms in D0 to at most three
clusters W1w11, ..., w1m, W2w21, ..., w2k
and W3w31, ..., w3j. 7. Formulate three
queries Q1-Q3 by combining W1-W3 with Q0 (for
example, Q1"w01 ... w0n w11 ... w1m"). 8. Get
document sets DT1-DT4 and D1-D3 by sending
QT1-QT4 and Q1-Q3 independently to a general
search engine. 9. Count co-occurrences in
DT1-DT4 and D1-D3. Sets of high co-occurrence
terms WTH1-WTH4 and WH1-WH3, as well as WH0 in
step 3, are query expansion results.
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Query Routing Result Query python
User query

• If you are looking for information about
• movie-monty python

Phrase to explain topic
1600 Search/Go to Search the Internet Movie
Database 1600 Search/Go to The Roger Ebert
Movie Files 1600 Search/Go to Horror Search
Recommended topic Search Engines
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Other Topics.
Object oriented programming in python 7500
Search/Go to Index to Object Oriented Information
Sources 3600 Search/Go to Unix Programming
jpython- python in java 6300 Search/Go to
java.sun.com The Source for Java
Technology 5641 Search/Go to Gamelan- The
official Java Directory 4921 Search/Go to
JCentral Search the web for Java 4266
Search/Go to Index to Object Oriented Information
Sources
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• Importance of Topic Centric Query Routing
• Query Routing Model is used.
• Query Routing model doesnt generate centroids.
• IT consists an off line pre-processing
  component and online interface.
• Offline Query Routing Model takes as input a
  set of search engines and creates for each
  engine, an approximate textual model of that
  engines content or scope.

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• Online Query Routing Model takes a user query
  as input and applies a novel query expansion
  technique to the query
• Then it clusters the output of the query
  expansion to suggest multiple topics that user
  may be interested in.
• Each topic is associated with a set of search
  engines, eg., Python

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• Query Expansion model has the ability to
  automatically obtain terms relevant to a query
  from the web.
• Using Query Expansion model, it is not
  necessary to maintain a massive dictionary of
  terms in a wide range of fields.

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Conclusion

• Topic centric query routing uses a query
  expansion model.
• Query expansion model obtains all the
  information necessary in query routing form the
  web.
• Thus Query routing model is an intelligent
  agent that uses the web as its knowledge and
  identifies topics of given queries dynamically
  by query expansion.