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In modern era people get more and more dependent on internet for every type of information. To extract user¿s interested access pattern of web click stream data, Web Usage Mining is an application of this type of techniques. Record of different web user¿s web using pattern are get stored in web log repository, which are great source of knowledge about user¿s navigation. With increasing the use of internet, number of web sites and web pages are increasing rapidly so web usage mining become problematic for many application such as design, personalization, analysis of traffic, usability-studies, etc. But analyze and discovering user¿s interesting patterns are necessary for web administrator and recommendation system. In this, mining techniques are applied to web data for finding user¿s interesting patterns. That means in which patterns user want to access web pages and web-sites. This work is focus on graph based web usage mining. Normally this technique consume more time if data is available in huge amount. Hence an approach has been made to reduce the time complexity in efficient manner. We make the use of new graph based approach for mine user behaviour.
| Autorius: | Ankur Shah, Hemraj Varachhia, |
| Leidėjas: | LAP LAMBERT Academic Publishing |
| Išleidimo metai: | 2014 |
| Knygos puslapių skaičius: | 60 |
| ISBN-10: | 3659666092 |
| ISBN-13: | 9783659666094 |
| Formatas: | 220 x 150 x 4 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Graph Based Web Recommendation System to Improve Time Efficiency“
