Summary
An Electronic Performance Support System (EPSS) introduces challenges on contextualized and personalized information delivery. Recommender systems aim at delivering and suggesting relevant information according to users preferences, thus EPSSs could take advantage of the recommendation algorithms that have the effect of guiding users in a large space of possible options. The JUMP project1 aims at integrating an EPSS with a hybrid recommender system. Collaborative and content-based filtering are the recommendation techniques most widely adopted to date. The main contribution of this paper is a content-collaborative hybrid recommender which computes similarities between users relying on their content-based profiles in which user preferences are stored, instead of comparing their rating styles. A distinctive feature of our system is that a statistical model of the user interests is obtained by machine learning techniques integrated with linguistic knowledge contained in WordNet. This model, named "semantic user profile", is exploited by the hybrid recommender in the neighborhood formation process.
See the full content of this document
Extract
An Electronic Performance Support System Based On a Hybrid Content-Collaborative Recommender System
1. Background and Motivations
An Electronic Performance Support System (EPSS) provides solutions to fulfill informative needs related to the accomplishment of job tasks. It provides help, advices, demonstrations or any other support which a user needs in some day-today working environment [5, 26].While generic queries can be easily fulfilled with standard information retrieval tools, such as general purpose search engines, the scenario is more difficult if the search goal concerns grey information stored in various forms and spread in different company knowledge bases, managed by distinct applications, all running within the company intranet. It is the case of corporate information managed by users who have the background knowledge necessary to accomplish most of the tasks they have in charge, even if they lack some detailed information. This kind of tasks are neither generally coded in corporate procedures nor completely new to the worker.The goal of an EPSS consists in delivering contextualized and personalized information, acting ideally as an agent gluing together different information sources by means of semantic connections, and providing the user with contents tailored to the task being accomplished and to the characteristics of the user herself. Recommender systems [9] aim at delivering and suggestin...See the full content of this document
Sponsored links
