Abstract
The tremendous growth in the amount of information available poses some key challenges for information filtering and retrieval. Users not only expect high quality and relevant information, but also wish that the information be presented in an as efficient way as possible. The traditional filtering methods, however, only consider the relevant values of document. These conventional methods fail to consider the efficiency of documents retrieval. In this paper, we propose a new algorithm to calculate pn index called document similarity score based on elements of the document. Using the index, document profile will be derived. Any documents with the similarity score above a given threshold wilt be clustered. Using these pre-clusiered documents, information filtering and retrieval can be made more efficient. Experimental results clearly show our proposed method tremendously improves the efficiency of information filtering and retrieval. We also give an example application of our proposed method in business processes.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of INMIC 2004 - 8th International Multitopic Conference |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 743-748 |
| Number of pages | 6 |
| ISBN (Electronic) | 0780386809, 9780780386808 |
| DOIs | |
| Publication status | Published - 2004 |
| Event | 8th International Multitopic Conference, INMIC 2004 - Lahore, Pakistan Duration: Dec 24 2004 → Dec 26 2004 |
Other
| Other | 8th International Multitopic Conference, INMIC 2004 |
|---|---|
| Country | Pakistan |
| City | Lahore |
| Period | 12/24/04 → 12/26/04 |
Fingerprint
Keywords
- Business process
- Clustering
- Elements
- Information filtering
- Information retrieval
- Search engine
- Web crawlers
- World Wide Web
ASJC Scopus subject areas
- Engineering(all)
- Computer Science(all)
Cite this
Similarity score for information filtering thresholds in business processes. / Lai, Jun; Son, Ben; Ali, Saqib.
Proceedings of INMIC 2004 - 8th International Multitopic Conference. Institute of Electrical and Electronics Engineers Inc., 2004. p. 743-748 1492988.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Similarity score for information filtering thresholds in business processes
AU - Lai, Jun
AU - Son, Ben
AU - Ali, Saqib
PY - 2004
Y1 - 2004
N2 - The tremendous growth in the amount of information available poses some key challenges for information filtering and retrieval. Users not only expect high quality and relevant information, but also wish that the information be presented in an as efficient way as possible. The traditional filtering methods, however, only consider the relevant values of document. These conventional methods fail to consider the efficiency of documents retrieval. In this paper, we propose a new algorithm to calculate pn index called document similarity score based on elements of the document. Using the index, document profile will be derived. Any documents with the similarity score above a given threshold wilt be clustered. Using these pre-clusiered documents, information filtering and retrieval can be made more efficient. Experimental results clearly show our proposed method tremendously improves the efficiency of information filtering and retrieval. We also give an example application of our proposed method in business processes.
AB - The tremendous growth in the amount of information available poses some key challenges for information filtering and retrieval. Users not only expect high quality and relevant information, but also wish that the information be presented in an as efficient way as possible. The traditional filtering methods, however, only consider the relevant values of document. These conventional methods fail to consider the efficiency of documents retrieval. In this paper, we propose a new algorithm to calculate pn index called document similarity score based on elements of the document. Using the index, document profile will be derived. Any documents with the similarity score above a given threshold wilt be clustered. Using these pre-clusiered documents, information filtering and retrieval can be made more efficient. Experimental results clearly show our proposed method tremendously improves the efficiency of information filtering and retrieval. We also give an example application of our proposed method in business processes.
KW - Business process
KW - Clustering
KW - Elements
KW - Information filtering
KW - Information retrieval
KW - Search engine
KW - Web crawlers
KW - World Wide Web
UR - http://www.scopus.com/inward/record.url?scp=84935115300&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84935115300&partnerID=8YFLogxK
U2 - 10.1109/INMIC.2004.1492988
DO - 10.1109/INMIC.2004.1492988
M3 - Conference contribution
AN - SCOPUS:84935115300
SP - 743
EP - 748
BT - Proceedings of INMIC 2004 - 8th International Multitopic Conference
PB - Institute of Electrical and Electronics Engineers Inc.
ER -