Improving document relevancy using integrated language modeling techniques
This paper presents an integrated language model to improve document relevancy for text-queries. To be precise, an integrated stemming-lemmatization (S-L) model was developed and its retrieval performance was compared at three document levels, that is, at top 5, 10 and 15. A prototype search engine...
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| Format: | Article |
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Faculty of Computer Science and Information Technology, University of Malaya
2016
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| _version_ | 1825721116697559040 |
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| author | Balakrishnan, Vimala Humaidi, N. Lloyd-Yemoh, E. |
| author_facet | Balakrishnan, Vimala Humaidi, N. Lloyd-Yemoh, E. |
| author_sort | Balakrishnan, Vimala |
| collection | UM |
| description | This paper presents an integrated language model to improve document relevancy for text-queries. To be precise, an integrated stemming-lemmatization (S-L) model was developed and its retrieval performance was compared at three document levels, that is, at top 5, 10 and 15. A prototype search engine was developed and fifteen queries were executed. The mean average precisions revealed the S-L model to outperform the baseline (i.e. no language processing), stemming and also the lemmatization models at all three levels of the documents. These results were also supported by the histogram precisions which illustrated the integrated model to improve the document relevancy. However, it is to note that the precision differences between the various models were insignificant. Overall the study found that when language processing techniques, that is, stemming and lemmatization are combined, more relevant documents are retrieved. |
| first_indexed | 2024-03-06T05:45:28Z |
| format | Article |
| id | um.eprints-18453 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:45:28Z |
| publishDate | 2016 |
| publisher | Faculty of Computer Science and Information Technology, University of Malaya |
| record_format | dspace |
| spelling | um.eprints-184532020-01-08T07:41:38Z http://eprints.um.edu.my/18453/ Improving document relevancy using integrated language modeling techniques Balakrishnan, Vimala Humaidi, N. Lloyd-Yemoh, E. HF Commerce QA75 Electronic computers. Computer science This paper presents an integrated language model to improve document relevancy for text-queries. To be precise, an integrated stemming-lemmatization (S-L) model was developed and its retrieval performance was compared at three document levels, that is, at top 5, 10 and 15. A prototype search engine was developed and fifteen queries were executed. The mean average precisions revealed the S-L model to outperform the baseline (i.e. no language processing), stemming and also the lemmatization models at all three levels of the documents. These results were also supported by the histogram precisions which illustrated the integrated model to improve the document relevancy. However, it is to note that the precision differences between the various models were insignificant. Overall the study found that when language processing techniques, that is, stemming and lemmatization are combined, more relevant documents are retrieved. Faculty of Computer Science and Information Technology, University of Malaya 2016 Article PeerReviewed Balakrishnan, Vimala and Humaidi, N. and Lloyd-Yemoh, E. (2016) Improving document relevancy using integrated language modeling techniques. Malaysian Journal of Computer Science, 29 (1). pp. 45-55. ISSN 0127-9084, DOI https://doi.org/10.22452/mjcs.vol29no1.4 <https://doi.org/10.22452/mjcs.vol29no1.4>. https://doi.org/10.22452/mjcs.vol29no1.4 doi:10.22452/mjcs.vol29no1.4 |
| spellingShingle | HF Commerce QA75 Electronic computers. Computer science Balakrishnan, Vimala Humaidi, N. Lloyd-Yemoh, E. Improving document relevancy using integrated language modeling techniques |
| title | Improving document relevancy using integrated language modeling techniques |
| title_full | Improving document relevancy using integrated language modeling techniques |
| title_fullStr | Improving document relevancy using integrated language modeling techniques |
| title_full_unstemmed | Improving document relevancy using integrated language modeling techniques |
| title_short | Improving document relevancy using integrated language modeling techniques |
| title_sort | improving document relevancy using integrated language modeling techniques |
| topic | HF Commerce QA75 Electronic computers. Computer science |
| work_keys_str_mv | AT balakrishnanvimala improvingdocumentrelevancyusingintegratedlanguagemodelingtechniques AT humaidin improvingdocumentrelevancyusingintegratedlanguagemodelingtechniques AT lloydyemohe improvingdocumentrelevancyusingintegratedlanguagemodelingtechniques |