نتایج جستجو برای: recommendation systems
تعداد نتایج: 1210479 فیلتر نتایج به سال:
Point-of-interest (POI) recommendation that suggests new places for users to visit arises with the popularity of location-based social networks (LBSNs). Due to the importance of POI recommendation in LBSNs, it has attracted much academic and industrial interest. In this paper, we offer a systematic review of this field, summarizing the contributions of individual efforts and exploring their rel...
With the rapid expansion of the information on the Internet, recommender systems play an important role in terms of trade and research. Recommender systems try to guess the user's way of thinking, using the in-formation of user's behavior or similar users and their views, to discover and then propose a product which is the most appropriate and closest product of user's interest. In the past dec...
Due the success of emerging Web 2.0, and different social network Web sites such as Amazon and movie lens, recommender systems are creating unprecedented opportunities to help people browsing the web when looking for relevant information, and making choices. Generally, these recommender systems are classified in three categories: content based, collaborative filtering, and hybrid based recommen...
Recommendation systems aim to recommend items or packages of items that are likely to be of interest to users. Previous work on recommendation systems has mostly focused on recommending points of interest (POI), to identify and suggest top-k items or packages that meet selection criteria and satisfy compatibility constraints on items in a package, prior work, this paper investigates two issues ...
Current electronic commerce recommendation system is designed for single electronic commerce website and current recommendation technologies have obvious deficiencies Centralized recommendation systems can not resolve the contradiction between high recommendation quality and timely response, as well as that between limited recommendation range and ever rich information on the web. Distributed r...
The most common problems that arise when working with big data for intelligent production are analyzed in the article. work of recommendation systems finding relevant user information was considered. features singular-value decomposition (SVD) and Funk SVD algorithms reducing dimensionality providing quick recommendations were determined. An improvement algorithm using a smaller required amount...
Recommendation systems play a key role in everyday life; they are used to suggest items that selected among many candidates usually belong huge datasets. The recommendations require good performance both terms of speed and the effectiveness provided suggestions. At same time, one most challenging approaches computer science is quantum computing. This computational paradigm can provide significa...
Recommender Systems have evolved as an answer to information overload problem prevalent with online users, looking for relevant information out of a huge premise of content available online. Such systems are used to provide recommendations to the users guiding them towards items that match their interest areas and choice. News Recommendation is a specific research area under recommender systems...
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