Paradox in applications of semantic similarity models in information retrieval
Semantic similarity models are a series of mathematical models for computing semantic similarity values among nodes in a semantic net. In this paper we reveal the paradox in the applications of these semantic similarity models in the field of information retrieval, which is that these models rely on...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Conference Paper |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2008
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/10921 |
| _version_ | 1848747666839699456 |
|---|---|
| author | Dong, Hai Hussain, Farookh Khadeer Chang, Elizabeth |
| author2 | Ulieru. M. |
| author_facet | Ulieru. M. Dong, Hai Hussain, Farookh Khadeer Chang, Elizabeth |
| author_sort | Dong, Hai |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Semantic similarity models are a series of mathematical models for computing semantic similarity values among nodes in a semantic net. In this paper we reveal the paradox in the applications of these semantic similarity models in the field of information retrieval, which is that these models rely on a common prerequisite ? the words of a user query must correspond to the nodes of a semantic net. In certain situations, this sort of correspondence cannot be carried out, which invalidates the further working of these semantic similarity models. By means of two case studies, we analyze these issues. In addition, we discuss some possible solutions in order to address these issues. Conclusion and future works are drawn in the final section. |
| first_indexed | 2025-11-14T06:52:47Z |
| format | Conference Paper |
| id | curtin-20.500.11937-10921 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:52:47Z |
| publishDate | 2008 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-109212021-03-17T08:35:59Z Paradox in applications of semantic similarity models in information retrieval Dong, Hai Hussain, Farookh Khadeer Chang, Elizabeth Ulieru. M. information retrieval semantic similarity models semantic net Semantic similarity models are a series of mathematical models for computing semantic similarity values among nodes in a semantic net. In this paper we reveal the paradox in the applications of these semantic similarity models in the field of information retrieval, which is that these models rely on a common prerequisite ? the words of a user query must correspond to the nodes of a semantic net. In certain situations, this sort of correspondence cannot be carried out, which invalidates the further working of these semantic similarity models. By means of two case studies, we analyze these issues. In addition, we discuss some possible solutions in order to address these issues. Conclusion and future works are drawn in the final section. 2008 Conference Paper http://hdl.handle.net/20.500.11937/10921 Institute of Electrical and Electronics Engineers (IEEE) restricted |
| spellingShingle | information retrieval semantic similarity models semantic net Dong, Hai Hussain, Farookh Khadeer Chang, Elizabeth Paradox in applications of semantic similarity models in information retrieval |
| title | Paradox in applications of semantic similarity models in information retrieval |
| title_full | Paradox in applications of semantic similarity models in information retrieval |
| title_fullStr | Paradox in applications of semantic similarity models in information retrieval |
| title_full_unstemmed | Paradox in applications of semantic similarity models in information retrieval |
| title_short | Paradox in applications of semantic similarity models in information retrieval |
| title_sort | paradox in applications of semantic similarity models in information retrieval |
| topic | information retrieval semantic similarity models semantic net |
| url | http://hdl.handle.net/20.500.11937/10921 |