Text mining tool for ontology engineering based on use of product taxonomy and web directory

1
Text mining tool for ontology engineering based
on use of product taxonomy and web directory

• Jan Nemrava and Vojtech Svatek
• Department of Information and Knowledge
  Engineering
• VSE Praha

2
Current state

• IE and Ontology learning are frequently discussed
  issues in the field of Semantic Web.
• Semi-automatic and automatic methods
  ontology-based extraction of information needed
• Web is great source for unstructured text

3
Task is

• Collect specific words verbs in our case that
  usually occur together with particular product
  category as support for ontology designers.
• Small and specialized ontologies concerning one
  product category and describing its frequent
  relations in common text.
• Make use of fulltext search engines and DMOZ
  directory for retrieving information
• And UNSPSC (United Nations Standard Products and
  Services Code) product catalogue

4

• Web directory are rarely valid taxonomies.
• It is easy to see that subheadings are often not
  specializations of headings
• Some of them are even not concepts (names of
  entities) but properties that implicitly restrict
  the extension of a preceding concept in the
  hierarchy. Consider for example
  .../Industries/Construction and
  Maintenance/Materials and Supplies/
  /Masonry_and_Stone/Natural Stone/International
  Sources/Mexico.

5
Proposal of method

• Obtain so called indicator verbs that
  characterize particular term (product category in
  our case) in UNSPSC.
• Particular terms will be then generalized and may
  mine verbs that are indicative for the upper
  level of these terms.
• join UNSPSC taxonomy and its list of products
  with content of company websites to gain valuable
  information about verbs that usually occur in one
  sentence with some product category from the
  taxonomy.
• Use hand classified web directories containing
  relevant web sites.

6
Task sequence decomposition

• Manually select UNSPSC product and corresponding
  product category from DMOZ Business branch
• Search in directory headings names
• Search in web site description
• Use fulltext
• 1) Input URL of DMOZ directory containing
  
  companies that manufacture desired product.
• Output List of URL of companies.
• 2) Input URL of company website
• Output List of web pages containing the
  target term.
• 3) Input Web page containing the term
• Output File with extracted sentences
  containing the term
• 4) Input Sentence with term.
• Output Tagged sentences
• 5) Input Verbs
• Output lemmatized, grouped and saved verbs

7
Experiment

• Handling equipment branch / UNSPSC product with
  corresponding DMOZ category
• Goal is find verbs
• common for most products.
• characterizing one branch of products
• specific for small group of products, or even
  only one product
• 7 product categories, 303 verbs collected that
  occurred 7300 times at web sites.

8
Experiment
9
Experiments

• some verbs are obvious to be entirely neutral and
  do not characterize the products at all. (be,
  have, provide and use)
• Some are connected with manufacturing(design,
  require, offer, make, contact, manufacture,
  develop, supply)
• activities describing manipulating with material.
  (handle, lift, install and move)

10
Experiments
11

• normalization
• Fij fij (Vtj / V)
• Crofts normalization moderates the effect of
  high-frequency verbs
• cf K (1 - K) fij / mij
• TF/IDF
• wij fij log2(N / n)

12
Problem remaining

• Automate assigning UNSPSC category to DMOZ
  category
• Some UNSPSC have no appropriate category leading
  in no or little web sites.
• Some categories are less informative

13

• Thank you!