Information Retrieval and Folksonomies together for Recommender Systems
نویسندگان
چکیده
The powerful and democratic activity of social tagging allows the wide set of Web users to add free annotations on resources. Tags express user interests, preferences and needs, but also automatically generate folksonomies. They can be considered as gold mine, especially for e-commerce applications, in order to provide effective recommendations. Thus, several recommender systems exploit folksonomies in this context. Folksonomies have also been involved in many information retrieval approaches. In considering that information retrieval and recommender systems are siblings, we notice that few works deal with the integration of their approaches, concepts and techniques to improve recommendation. This paper is a first attempt in this direction. We propose a trail through recommender systems, social Web, e-commerce and social commerce, tags and information retrieval: an overview on the methodologies, and a survey on folksonomy-based information retrieval from recommender systems point of view, delineating a set of open and new perspectives.
منابع مشابه
Context-Aware Recommender Systems: A Review of the Structure Research
Recommender systems are a branch of retrieval systems and information matching, which through identifying the interests and requires of the user, help the users achieve the desired information or service through a massive selection of choices. In recent years, the recommender systems apply describing information in the terms of the user, such as location, time, and task, in order to produce re...
متن کاملA New Similarity Measure Based on Item Proximity and Closeness for Collaborative Filtering Recommendation
Recommender systems utilize information retrieval and machine learning techniques for filtering information and can predict whether a user would like an unseen item. User similarity measurement plays an important role in collaborative filtering based recommender systems. In order to improve accuracy of traditional user based collaborative filtering techniques under new user cold-start problem a...
متن کاملGraph-based recommendation in broad folksonomies
The user-centric annotation of resources by freely chosen words (tags) has become the predominant form of content categorization of the Web 2.0 age. It provided the foundations for the success of now famous services, such as Delicious, Flickr, LibraryThing, or Last.fm. Tags have proven to be a powerful alternative to existing top-down categorization techniques, as for example taxonomies or pred...
متن کاملImproving Accuracy of Recommender Systems using Social Network Information and Longitudinal Data
The rapid development of technology, the Internet, and the development of electronic commerce have led to the emergence of recommender systems. These systems will assist the users in finding and selecting their desired items. The accuracy of the advice in recommender systems is one of the main challenges of these systems. Regarding the fuzzy systems capabilities in determining the borders of us...
متن کاملThe Feasibility Study of Launching Book Recommendation System on the Basis of a Lending and Selling System of e-Books and Digital Taktab
Background:The study was conducted to achieve three axes of goals (users, publishers and the system) by way of objectives related to: A) Users - measuring the level of their satisfaction with Taktab system and also use of various methods of data retrieval; B) Publishers - Measuring the level of their satisfaction with Taktab system and also their expectations of the existence of a recommending...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2011