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Intelligent classification of web pages using contextual and visual features
, Article Applied Soft Computing Journal ; Volume 11, Issue 2 , 2011 , Pages 1638-1647 ; 15684946 (ISSN) ; Fotouhi, M ; Khaleghi, M ; Sharif University of Technology
Abstract
In this paper we address classification of Web content and in particular its application in the detection of pornographic Web pages. Filtering of undesirable Web content is mainly achieved based on blocking a specific Web address via searching it in a reference list of black URLs or doing a plain contextual analysis on the page by searching special keywords in the text. The main problem with current filtering methods is the requirement for instantly update of the URL list and also the high rate of over-blocking the usual pages. In this paper, we propose an intelligent approach which is based on using textual, profile, and visual features in a hierarchical structure classifier. Textual...
DWM-CDD: Dynamic weighted majority concept drift detection for spam mail filtering
, Article World Academy of Science, Engineering and Technology ; Volume 80 , 2011 , Pages 291-294 ; 2010376X (ISSN) ; Pour, A. N ; Sharif University of Technology
Abstract
Although e-mail is the most efficient and popular communication method, unwanted and mass unsolicited e-mails, also called spam mail, endanger the existence of the mail system. This paper proposes a new algorithm called Dynamic Weighted Majority Concept Drift Detection (DWM-CDD) for content-based filtering. The design purposes of DWM-CDD are first to accurate the performance of the previously proposed algorithms, and second to speed up the time to construct the model. The results show that DWM-CDD can detect both sudden and gradual changes quickly and accurately. Moreover, the time needed for model construction is less than previously proposed algorithms
Hybrid Design of Recommender Systems
, M.Sc. Thesis Sharif University of Technology ; Izadi, Mohammad (Supervisor)
Abstract
Nowadays recommender systems are one of the most important parts of big websites. These systems help users to find their intended items among enormous amounts of data. Traditionally, recommender systems are designed and implemented using different methods such as content based, collaborative and demographic filtering. Each of these methods had some problems that lead to emergence of a new kind of recommender systems called hybrid recommender systems. This kind of recommender systems try to combine the other methods and make them better. In this thesis, we have selected some previous recommender systems and then, we have made a new system by combining and reforming them. The resulted...
Design a Recommender System for Purchasing Cosmetics using Text Mining Methods
, M.Sc. Thesis Sharif University of Technology ; Rafiee, Majid (Supervisor)
Abstract
In recent years, the cosmetics industry has dramatically grown in e-commerce. In e-commerce platforms, where multiple choices are available, an efficient recommender system is required to sort, order, and effectively transfer relevant content or product information to users. Recommender systems have attracted a lot of attention from retailers because they provide consumers with a personalized shopping experience. With technological advancements, this branch of artificial intelligence exhibits great potential in imaging, analysis, classification, and segmentation. Despite the great potential, the academic articles in this field are limited. Therefore, we conducted research in this context, in...