The study of probability model for compound similarity searching
Information Retrieval or IR system main task is to retrieve relevant documents according to the users query. One of IR most popular retrieval model is the Vector Space Model. This model assumes relevance based on similarity, which is defined as the distance between query and document in the concept...
| Main Authors: | , , , |
|---|---|
| Format: | Monograph |
| Language: | English |
| Published: |
Faculty of Computer Science and Information System
2006
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/4267/ http://eprints.utm.my/4267/1/75207.pdf |
| _version_ | 1848890758574112768 |
|---|---|
| author | Salim, Naomie Abd. Wahid, Mohd. Taib Alwee, Razana Dollah @ Md. Zain, Rozilawati |
| author_facet | Salim, Naomie Abd. Wahid, Mohd. Taib Alwee, Razana Dollah @ Md. Zain, Rozilawati |
| author_sort | Salim, Naomie |
| building | UTeM Institutional Repository |
| collection | Online Access |
| description | Information Retrieval or IR system main task is to retrieve relevant documents according to the users query. One of IR most popular retrieval model is the Vector Space Model. This model assumes relevance based on similarity, which is defined as the distance between query and document in the concept space. All currently existing chemical compound database systems have adapt the vector space model to calculate the similarity of a database entry to a query compound. However, it assumes that fragments represented by the bits are independent of one another, which is not necessarily true. Hence, the possibility of applying another IR model is explored, which is the Probabilistic Model, for chemical compound searching. This model estimates the probabilities of a chemical structure to have the same bioactivity as a target compound. It is envisioned that by ranking chemical structures in decreasing order of their probability of relevance to the query structure, the effectiveness of a molecular similarity searching system can be increased. Both fragment dependencies and independencies assumption are taken into consideration in achieving improvement towards compound similarity searching system. After conducting a series of simulated similarity searching, it is concluded that PM approaches really did perform better than the existing similarity searching. It gave better result in all evaluation criteria to confirm this statement. In terms of which probability model performs better, the BD model shown improvement over the BIR model. |
| first_indexed | 2025-11-15T20:47:10Z |
| format | Monograph |
| id | utm-4267 |
| institution | Universiti Teknologi Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:47:10Z |
| publishDate | 2006 |
| publisher | Faculty of Computer Science and Information System |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utm-42672017-08-07T01:31:41Z http://eprints.utm.my/4267/ The study of probability model for compound similarity searching Salim, Naomie Abd. Wahid, Mohd. Taib Alwee, Razana Dollah @ Md. Zain, Rozilawati QA75 Electronic computers. Computer science Information Retrieval or IR system main task is to retrieve relevant documents according to the users query. One of IR most popular retrieval model is the Vector Space Model. This model assumes relevance based on similarity, which is defined as the distance between query and document in the concept space. All currently existing chemical compound database systems have adapt the vector space model to calculate the similarity of a database entry to a query compound. However, it assumes that fragments represented by the bits are independent of one another, which is not necessarily true. Hence, the possibility of applying another IR model is explored, which is the Probabilistic Model, for chemical compound searching. This model estimates the probabilities of a chemical structure to have the same bioactivity as a target compound. It is envisioned that by ranking chemical structures in decreasing order of their probability of relevance to the query structure, the effectiveness of a molecular similarity searching system can be increased. Both fragment dependencies and independencies assumption are taken into consideration in achieving improvement towards compound similarity searching system. After conducting a series of simulated similarity searching, it is concluded that PM approaches really did perform better than the existing similarity searching. It gave better result in all evaluation criteria to confirm this statement. In terms of which probability model performs better, the BD model shown improvement over the BIR model. Faculty of Computer Science and Information System 2006-09-30 Monograph NonPeerReviewed application/pdf en http://eprints.utm.my/4267/1/75207.pdf Salim, Naomie and Abd. Wahid, Mohd. Taib and Alwee, Razana and Dollah @ Md. Zain, Rozilawati (2006) The study of probability model for compound similarity searching. Project Report. Faculty of Computer Science and Information System, Skudai, Johor. (Unpublished) |
| spellingShingle | QA75 Electronic computers. Computer science Salim, Naomie Abd. Wahid, Mohd. Taib Alwee, Razana Dollah @ Md. Zain, Rozilawati The study of probability model for compound similarity searching |
| title | The study of probability model for compound similarity searching |
| title_full | The study of probability model for compound similarity searching |
| title_fullStr | The study of probability model for compound similarity searching |
| title_full_unstemmed | The study of probability model for compound similarity searching |
| title_short | The study of probability model for compound similarity searching |
| title_sort | study of probability model for compound similarity searching |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.utm.my/4267/ http://eprints.utm.my/4267/1/75207.pdf |