Ontological Classification of Web Pages

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• Ontological Classification of Web Pages
• Zafer Erenel
• Many users use search engines to locate and buy
  goods and services (such as choosing a vacation).
  
• Web pages presented on the internet do not
  conform to any data organization standard and
  search engines provide primitive query
  capabilities for users to retrieve relevant data
  1.
• In addition to that, they do not list sites
  equally and are inclined toward listing more
  popular pages. These tendencies brush many web
  pages aside and leave a limited number of
  alternatives to the users.I have created a
  lightweight domain ontology that consists of a
  taxonomic hierarchy and made use of it by an
  automated agent to classify web pages on the
  internet.
• The automated agent discovers and classifies
  relevant pages with the help of Yahoo and Google
  search engines.

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• Related Research
• Desai and Spink presented a clustering scheme
  that groups documents into partially and
  substantially relevant pages by using similarity
  measures and ranking heuristics 2.
• They worked with the end-user queries (limited
  number of terms) to obtain the relevance score.
  Instead, my automated agent will act along with
  an established ontology to discover and classify
  documents.
• Chiang, Chua, and Storey parsed snippets of
  returned links to find the ratio of the number of
  matching terms to rank the web pages for
  relevance 1.
• I believe snippets consist of a very few number
  of words and we cannot judge the web page on the
  basis of snippets. My agent scours the entire web
  page which is more time-consuming but more
  effective

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• Yahoo and Google search results contain scores of
  links.
• My lightweight domain ontology consists of 7
  branches. Each branch is comprised of
  predetermined terms.
• Score of the web page increases in a certain
  branch as the agent comes across these
  predetermined terms on the html code.
• Ive chosen country ontology because internet
  users interest in a certain country can be quite
  high.

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• The ranks of web pages in each cluster will
  clarify their content to the user.
• In addition to that, we can compare result sets
  of different search engines (Yahoo and Google)
  for the same queries and find complement and
  intersection of their result sets to have a clear
  understanding of search engines behaviors.

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• Ive used web stream classes in C Programming
  language to create my agent.
• A WebRequest is an object that requests a Uniform
  Resource Identifier (URI) such as the URL for a
  web page 3.
• You can use a WebRequest object to create a
  WebResponse object that will encapsulate the
  object pointed to by the URI.
• Once you get the actual object (e.g., a web page)
  pointed to by the URI, what you get back is a
  stream of the web page.

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• I used this capability for reading a page from a
  site to extract the information I need. I have
  created two web requests using search syntax
  given below

• http//www.google.com/search?qcyprusvacationtra
  vellrstart0saN
• http//search.yahoo.com/search?pcyprusvacationt
  ravelb1

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• Google search engine has returned 200 URLs and I
  have created 200 web requests to extract relevant
  information from each web page.
• Yahoo search engine has been used in the same
  manner to extract relevant information.

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• If we analyze price rankings, we come across
  pages that have information about student
  flights, travel insurances, vacation package
  discounts, cheap flights and etc..
• If we analyze nature rankings, we come across web
  pages that offer adventure and etc.
• If I want to do scuba diving on my vacation, I
  know that hawai and fiji are among my options by
  looking at activities rankings

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• Interestingly enough, in the top 100 search
  lists, the number of web pages that both appear
  on Google and Yahoo is 19.

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• In the top 200 search lists, the number of web
  pages that both appear on Google and Yahoo is 24.

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• As a result, ontologically organized clusters of
  web sites that are offering information about a
  given country regarding vacation and travel
  alternatives serve our objective to a greater
  extent in finding what we are in search of.
• In my work, I have used 2 search engines and a
  single ontology. Search Engines shortcomings can
  be prevented by combining multiple engines with
  multiple ontologies to ease the search for most
  needed information on the internet.
• Venn Diagrams prove that a specific search engine
  is not very effective by itself.

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References 1 R.H.L. Chiang, C.E.H. Chua, V.C.
Storey, A smart web query method for semantic
retrieval of web data, Data Knowledge
Engineering 38 (2001) 63-84. 2 M. Desai, A.
Spink, An algorithm to cluster documents based on
relevance, Information Processing and Management
41 (2005) 1035-1049. 3 Liberty, J.,
Programming C,3rd ed. OREILLY, 2003.