Web Recommender System Implementations in Multiple Flavors: Fast and (Care-)Free for All
نویسندگان
چکیده
In this paper, we present a systematic framework for a fast and easy implementation and deployment of a recommendation system for one or several Websites, based on any available combination of open source tools that include crawling, indexing, and searching capabilities. The supported recommendation strategies include several popular flavors such as content based filtering (straight forward), collaborative filtering (more complex), rule-based, as well as approaches that deal with meta-content, (non-textual) attributes and ontologies, and other variants that include meta-attributes about the user, such as elaborate user profiles, as well as business strategy rules. The biggest advantage of this approach is that for content-based filtering, it allows client or proxy controlled integration of several websites.
منابع مشابه
Hybrid Adaptive Educational Hypermedia Recommender Accommodating User’s Learning Style and Web Page Features
Personalized recommenders have proved to be of use as a solution to reduce the information overload problem. Especially in Adaptive Hypermedia System, a recommender is the main module that delivers suitable learning objects to learners. Recommenders suffer from the cold-start and the sparsity problems. Furthermore, obtaining learner’s preferences is cumbersome. Most studies have only focused...
متن کاملIMPROVE THE RECOMMENDER SYSTEM USING SEMANTIC WEB
To buy his/her necessities such as books, movies, CD, music, etc., one always trusts others’ oral and written consultations and offers and include them in his/her decisions. Nowadays, regarding the progress of technologies and development of e-business in websites, a new age of digital life has been commenced with the Recommender systems. The most important objectives of these systems include a...
متن کاملUse of Semantic Similarity and Web Usage Mining to Alleviate the Drawbacks of User-Based Collaborative Filtering Recommender Systems
One of the most famous methods for recommendation is user-based Collaborative Filtering (CF). This system compares active user’s items rating with historical rating records of other users to find similar users and recommending items which seems interesting to these similar users and have not been rated by the active user. As a way of computing recommendations, the ultimate goal of the user-ba...
متن کاملModeling a Smart Hospital Information Architecture Based on Internet of Things and Recommender Agent
Introduction: Today, healthcare organizations worldwide are aware of the significance of technology and its impact on the quality of care. Hospitals are one of the most crucial systems in which the utilization of information is particularly important for several reasons. Using discrete-event simulation and developing a recommender agent, this study aimed to allocate IoT devices to patients in s...
متن کاملEvaluation of recommender systems: A multi-criteria decision making approach
The evaluation and selection of recommender systems is a difficult decision making process. This difficulty is partially due to the large diversity of published evaluation criteria in addition to lack of standardized methods of evaluation. As such, a systematic methodology is needed that explicitly considers multiple, possibly conflicting metrics and assists decision makers to evaluate and find...
متن کامل