| Type of Material: | Thesis |
| Title: | Studies on context aware trust based recommender system |
| Researcher: | PALLAB DUTTA |
| Guide: | KUMARAVEL |
| Department: | Department of Engineering and Technology(Computer Science and Engineering) |
| Publisher: | Bharath University, Chennai |
| Place: | Chennai |
| Year: | 2017 |
| Language: | English |
| Subject: | Weka Explorer | Collaborative Filtering | Markov Models | Computer Science and Information Technology | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; Department of Engineering and Technology(Computer Science and Engineering), Bharath University, Chennai, Chennai; 2017; D11CS012 |
| Fulltext: | Shodhganga |
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| 003 | IN-AhILN | |
| 005 | 2024-09-12 17:57:18 | |
| 008 | __ | 240912t2017||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_454531 |
| 040 | __ | |aBHAU_600073|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aPALLAB DUTTA|eResearcher |
| 110 | __ | |aDepartment of Engineering and Technology(Computer Science and Engineering)|bBharath University, Chennai|dChennai|ein |
| 245 | __ | |aStudies on context aware trust based recommender system |
| 260 | __ | |aChennai|bBharath University, Chennai|c2017 |
| 300 | __ | |dDVD |
| 502 | __ | |cDepartment of Engineering and Technology(Computer Science and Engineering), Bharath University, Chennai, Chennai|d2017|oD11CS012|bPhD |
| 518 | __ | |d23.06.2011|oDate of Registration |
| 520 | __ | |aLast couple of decades had been witnessed to an unprecedented expansion of Internet; huge amount of information is available in almost all domains and subjects and is ever expanding. This has resulted in data overloading; due to which it has become an increasing problem for retrieving useful information from internet. Users searching for products or content have endless number of Web pages to navigate and require enormous efforts, requires judgmental aptitude and intuitiveness to extract meaningful information from the ever expanding web of data. Recommender systems are meant to be an important solution to the data overload problem that persists today in World Wide Web. The job of the recommender system is to provide the consumer with a selection of products or content which suit his/her needs so that the user are relived from the herculean task of browsing through enormous number of web pages. Recommender system has undergone a lot of improvements from the time of its conceptualization and inception in ter |
| 650 | __ | |aComputer Science and Information Technology|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aWeka Explorer |
| 653 | __ | |aCollaborative Filtering |
| 653 | __ | |aMarkov Models |
| 700 | __ | |aKUMARAVEL|eGuide |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/170890|yShodhganga |
| 905 | __ | |afromsg |
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