Improving Search on Web Directory by Introducing Ontologies

Transcription

1 Improving Search on Web Directory by Introducing Ontologies Gordan Gledec, Maja Matijašević, Damir Jurić Department of Telecommunications Faculty of Electrical Engineering and Computing, University of Zagreb, Croatia 9th International Conference on Knowledge-Based & Intelligent Information & Engineering Systems, Melbourne, Australia

2 KES 2005, Melbourne, Australia 2 / 14 Outline Motivation About Croatian Web directory Search mechanism Proposed ontology-based improvements Building the ontology Implementation Results Conclusion and future work

3 Motivation Croatian Web Directory (since 1994.) sites in 700+ categories visitors/month, 90+ GB traffic search queries problems with finding the information study on user queries (CUC 2004) problems related to the number and relevance of search results new search mechanisms are needed semantic search! solution introduce ontologies! KES 2005, Melbourne, Australia 3 / 14

4 KES 2005, Melbourne, Australia 4 / 14 Web directory & search the directory: organized into hierarchical structure similar to Yahoo and DMOZ 14 top categories, 700+ subcategories search info: site name, site description, site URL, category name, META keywords (extracted from URL) types of user queries all keywords (default and query) logical expressions (and, or, not, +, -) wildcards (* representing any keyword suffix) phrases (any string in quotation marks)

5 Study on user queries (2004) more than 60% of queries consist of a single term large number of matches (>20) 70% of all queries are nouns problems: no recall: almost 30% of queries return no relevant results low precission, high recall: almost 40% of queries return 15+ results vocabulary mismatch: results depend on the vocabulary (terms) users use in formulating their queries improvement expected with the introduction of ontologies KES 2005, Melbourne, Australia 5 / 14

6 KES 2005, Melbourne, Australia 6 / 14 Classical search user query results search engine

7 KES 2005, Melbourne, Australia 7 / 14 Ontology-based search user query ontology modification modified query results search engine

8 Building the ontology the directory is general, the user is a public user many domain-related ontologies have to be created guideline: knowledge of user behaviour and expectations process: domain consideration what should be included as part of the ontology? planning the domain knowledge: categories, user analysis, ontology creator (human) coding the ontology technically acceptable format W3C - OWL KES 2005, Melbourne, Australia 8 / 14

9 Implementation ontology tourism was created first Croatia is a tourist country, most frequently visited category sources: existing subcategorization of the Tourism and Traveling category keywords used by users in their queries META keywords from submitted sites human experience knowledge in the ontology represented by: subclasses of the query term alternative terms or synonyms upclasses and possible restrictions KES 2005, Melbourne, Australia 9 / 14

10 Ontology tourism KES 2005, Melbourne, Australia 10 / 14

11 Dummy user query modification interface KES 2005, Melbourne, Australia 11 / 14

12 Results problems addressed: low recall modifying the query by including all subclasses of the query term - more results retrieved (obviously ) high recall, low precission modifying the query by using the restrictions of the query term (eg. location) fewer results vocabulary mismatch query modified by including synonyms and alternative words extracted from the ontology more results (1) low recall (2) high recall, low precision >200 (3) vocabulary mismatch modified query original query (a) (b) (a) (b) (a) (b) KES 2005, Melbourne, Australia 12 / 14

13 KES 2005, Melbourne, Australia 13 / 14 Conclusion and future work to the best of our knowledge, this is the first study about ontology-based search improvements related to the Croatian language and Croatian Web space the approach and method applied is general and not language specific combining proposed methods may increase search efficiency in terms of recall, precision and relevance query expansion followed by restriction future: ontologies from other domains, improvement of user interface, performing user surveys to assess the relevance of search results

14 Thank you for the attention! BTW, visit