نتایج جستجو برای: aware recommender system
تعداد نتایج: 2287766 فیلتر نتایج به سال:
The advent of Digital TV has provided the growth in the volume of TV programs offered by TV operators. Consequently, the difficulty in finding the content the TV viewer wishes in a transparent way among the available TV programs increased. Within this scenario, the recommender systems stand out as a possible solution for this problem. However, the context has rarely been explored during the rec...
Mass customization of standardized products has become a trend to succeed in today’s market environment. Software Product Lines (SPLs) address this trend by describing a family of software products that share a common set of features. However, choosing the appropriate set of features that matches a user’s individual interests is hampered due to the overwhelming amount of possible SPL configurat...
Most existing approaches in Context-Aware Recommender Systems (CRS) focus on recommending relevant items to users taking into account contextual information, such as time, location, or social aspects. However, few of them have considered the problem of user’s content dynamicity. We introduce in this paper an algorithm that tackles the user’s content dynamicity by modeling the CRS as a contextua...
In many online applications, the range of content that is offered to users is so wide that a need for automated recommender systems arises. Such systems can provide a personalized selection of relevant items to users. In practice, this can help people find entertaining movies, boost sales through targeted advertisements, or help social network users meet new friends. To generate accurate person...
The user preference is dynamic and requires drift detection to capture changes for delivering relevant recommendations. A sequential recommender system with was proposed, where points are indicated by comparing characteristics of consecutive items. model leverages retrieve only interactions preferences the current preference. Nonetheless, number utilized items pre-defined may not be optimal. It...
As personal transportation is one of the greatest contributors of CO2 emissions, means able to assist travelers in reducing their ecological impact are urgently needed. In this work we focus on travel recommenders that encourage green transportation habits among travelers who have a preexisting interest in taking action to lessen their impact on the environment. We aim to provide urban traveler...
Recommender systems have shown great potential to help users find interesting and relevant Web service (WS) from within large registers. However, with the proliferation of WSs, recommendation becomes a very difficult task. Social computing seems offering innovative solutions to overcome those shortcomings. Social computing is at the crossroad of computer sciences and social sciences disciplines...
The revolution of World Wide Web (WWW) and smart-phone technologies have been the key-factor behind remarkable success of social networks. With the ease of availability of check-in data, the location-based social networks (LBSN) (e.g., Facebook, etc.) have been heavily explored in the past decade for Point-of-Interest (POI) recommendation. Though many POI recommenders have been defined, most of...
The development of methods that can enhance the creativity process is becoming a continuous necessity. Through the years several researchers modelled and defined creativity focusing to the psychological aspect of the topic. More recent researchers approach creativity as a computerized process by simulating it within creativity support tools (CST). This article supports that usage of context awa...
In this work we propose and study an approach for collaborative filtering, which is based on Boolean matrix factorisation and exploits additional (context) information about users and items. To avoid similarity loss in case of Boolean representation we use an adjusted type of projection of a target user to the obtained factor space. We have compared the proposed method with SVD-based approach o...
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