A fuzzy method for improving the functionality of search engines based on user's web interactions
Web mining has been widely used to discover knowledge from various sources in the web. One of the important tools in web mining is mining of web user’s behavior that is considered as a way to discover the potential knowledge of web user’s interaction. Nowadays, Website personalization is regarded as...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Growing Science
2015-04-01
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| Series: | Management Science Letters |
| Subjects: | |
| Online Access: | http://www.growingscience.com/msl/Vol5/msl_2015_25.pdf |
| _version_ | 1811330836506607616 |
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| author | Farzaneh Kabirbeyk Ali Harounabadi Mostafa Sabzekar |
| author_facet | Farzaneh Kabirbeyk Ali Harounabadi Mostafa Sabzekar |
| author_sort | Farzaneh Kabirbeyk |
| collection | DOAJ |
| description | Web mining has been widely used to discover knowledge from various sources in the web. One of the important tools in web mining is mining of web user’s behavior that is considered as a way to discover the potential knowledge of web user’s interaction. Nowadays, Website personalization is regarded as a popular phenomenon among web users and it plays an important role in facilitating user access and provides information of users’ requirements based on their own interests. Extracting important features about web user behavior plays a significant role in web usage mining. Such features are page visit frequency in each session, visit duration, and dates of visiting a certain pages. This paper presents a method to predict user’s interest and to propose a list of pages based on their interests by identifying user’s behavior based on fuzzy techniques called fuzzy clustering method. Due to the user’s different interests and use of one or more interest at a time, user’s interest may belong to several clusters and fuzzy clustering provide a possible overlap. Using the resulted cluster helps extract fuzzy rules. This helps detecting user’s movement pattern and using neural network a list of suggested pages to the users is provided. |
| first_indexed | 2024-04-13T16:09:56Z |
| format | Article |
| id | doaj.art-4d4a491698514c1da6086f6e2eb368c8 |
| institution | Directory Open Access Journal |
| issn | 1923-2934 1923-9343 |
| language | English |
| last_indexed | 2024-04-13T16:09:56Z |
| publishDate | 2015-04-01 |
| publisher | Growing Science |
| record_format | Article |
| series | Management Science Letters |
| spelling | doaj.art-4d4a491698514c1da6086f6e2eb368c82022-12-22T02:40:17ZengGrowing ScienceManagement Science Letters1923-29341923-93432015-04-015437738610.5267/j.msl.2015.2.008A fuzzy method for improving the functionality of search engines based on user's web interactionsFarzaneh KabirbeykAli HarounabadiMostafa SabzekarWeb mining has been widely used to discover knowledge from various sources in the web. One of the important tools in web mining is mining of web user’s behavior that is considered as a way to discover the potential knowledge of web user’s interaction. Nowadays, Website personalization is regarded as a popular phenomenon among web users and it plays an important role in facilitating user access and provides information of users’ requirements based on their own interests. Extracting important features about web user behavior plays a significant role in web usage mining. Such features are page visit frequency in each session, visit duration, and dates of visiting a certain pages. This paper presents a method to predict user’s interest and to propose a list of pages based on their interests by identifying user’s behavior based on fuzzy techniques called fuzzy clustering method. Due to the user’s different interests and use of one or more interest at a time, user’s interest may belong to several clusters and fuzzy clustering provide a possible overlap. Using the resulted cluster helps extract fuzzy rules. This helps detecting user’s movement pattern and using neural network a list of suggested pages to the users is provided.http://www.growingscience.com/msl/Vol5/msl_2015_25.pdfWeb PersonalizationRecommender SystemWeb Usage MiningFuzzy clustering |
| spellingShingle | Farzaneh Kabirbeyk Ali Harounabadi Mostafa Sabzekar A fuzzy method for improving the functionality of search engines based on user's web interactions Management Science Letters Web Personalization Recommender System Web Usage Mining Fuzzy clustering |
| title | A fuzzy method for improving the functionality of search engines based on user's web interactions |
| title_full | A fuzzy method for improving the functionality of search engines based on user's web interactions |
| title_fullStr | A fuzzy method for improving the functionality of search engines based on user's web interactions |
| title_full_unstemmed | A fuzzy method for improving the functionality of search engines based on user's web interactions |
| title_short | A fuzzy method for improving the functionality of search engines based on user's web interactions |
| title_sort | fuzzy method for improving the functionality of search engines based on user s web interactions |
| topic | Web Personalization Recommender System Web Usage Mining Fuzzy clustering |
| url | http://www.growingscience.com/msl/Vol5/msl_2015_25.pdf |
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