Effective Filtering of Query Results on Updated User Behavioral Profiles in Web Mining
Web with tremendous volume of information retrieves result for user related queries. With the rapid growth of web page recommendation, results retrieved based on data mining techniques did not offer higher performance filtering rate because relationships between user profile and queries were not ana...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2015/829126 |
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| author | S. Sadesh R. C. Suganthe |
| author_facet | S. Sadesh R. C. Suganthe |
| author_sort | S. Sadesh |
| collection | DOAJ |
| description | Web with tremendous volume of information retrieves result for user related queries. With the rapid growth of web page recommendation, results retrieved based on data mining techniques did not offer higher performance filtering rate because relationships between user profile and queries were not analyzed in an extensive manner. At the same time, existing user profile based prediction in web data mining is not exhaustive in producing personalized result rate. To improve the query result rate on dynamics of user behavior over time, Hamilton Filtered Regime Switching User Query Probability (HFRS-UQP) framework is proposed. HFRS-UQP framework is split into two processes, where filtering and switching are carried out. The data mining based filtering in our research work uses the Hamilton Filtering framework to filter user result based on personalized information on automatic updated profiles through search engine. Maximized result is fetched, that is, filtered out with respect to user behavior profiles. The switching performs accurate filtering updated profiles using regime switching. The updating in profile change (i.e., switches) regime in HFRS-UQP framework identifies the second- and higher-order association of query result on the updated profiles. Experiment is conducted on factors such as personalized information search retrieval rate, filtering efficiency, and precision ratio. |
| format | Article |
| id | doaj-art-866a8dcdcc7b471db2ebf6bdad6ad7be |
| institution | OA Journals |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-866a8dcdcc7b471db2ebf6bdad6ad7be2025-08-20T02:08:47ZengWileyThe Scientific World Journal2356-61401537-744X2015-01-01201510.1155/2015/829126829126Effective Filtering of Query Results on Updated User Behavioral Profiles in Web MiningS. Sadesh0R. C. Suganthe1Velalar College of Engineering and Technology, Thindal, Tamil Nadu, IndiaKongu Engineering College, Perundurai, Tamil Nadu, IndiaWeb with tremendous volume of information retrieves result for user related queries. With the rapid growth of web page recommendation, results retrieved based on data mining techniques did not offer higher performance filtering rate because relationships between user profile and queries were not analyzed in an extensive manner. At the same time, existing user profile based prediction in web data mining is not exhaustive in producing personalized result rate. To improve the query result rate on dynamics of user behavior over time, Hamilton Filtered Regime Switching User Query Probability (HFRS-UQP) framework is proposed. HFRS-UQP framework is split into two processes, where filtering and switching are carried out. The data mining based filtering in our research work uses the Hamilton Filtering framework to filter user result based on personalized information on automatic updated profiles through search engine. Maximized result is fetched, that is, filtered out with respect to user behavior profiles. The switching performs accurate filtering updated profiles using regime switching. The updating in profile change (i.e., switches) regime in HFRS-UQP framework identifies the second- and higher-order association of query result on the updated profiles. Experiment is conducted on factors such as personalized information search retrieval rate, filtering efficiency, and precision ratio.http://dx.doi.org/10.1155/2015/829126 |
| spellingShingle | S. Sadesh R. C. Suganthe Effective Filtering of Query Results on Updated User Behavioral Profiles in Web Mining The Scientific World Journal |
| title | Effective Filtering of Query Results on Updated User Behavioral Profiles in Web Mining |
| title_full | Effective Filtering of Query Results on Updated User Behavioral Profiles in Web Mining |
| title_fullStr | Effective Filtering of Query Results on Updated User Behavioral Profiles in Web Mining |
| title_full_unstemmed | Effective Filtering of Query Results on Updated User Behavioral Profiles in Web Mining |
| title_short | Effective Filtering of Query Results on Updated User Behavioral Profiles in Web Mining |
| title_sort | effective filtering of query results on updated user behavioral profiles in web mining |
| url | http://dx.doi.org/10.1155/2015/829126 |
| work_keys_str_mv | AT ssadesh effectivefilteringofqueryresultsonupdateduserbehavioralprofilesinwebmining AT rcsuganthe effectivefilteringofqueryresultsonupdateduserbehavioralprofilesinwebmining |