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Recommender System Based on Workflow

Author: SunHu
Tutor: TuFengHua
School: Chongqing University
Course: Applied Computer Technology
Keywords: Recommendation System Workflow Collaborative Filtering Information Management
CLC: TP391.3
Type: Master's thesis
Year: 2012
Downloads: 36
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Abstract


In today’s society Internet technology has been used widely, this will drive the electronicbusiness today’s rapid development, but also led to the Internet resources quantity to grow at arapid pace."The information explosion" and "information overload" make people in the face ofthe vast amount of information content, often feel overwhelmed, they find it hard to foundhimself really need information. People put forward many ways to try to solve the informationoverload, then we is now widely used the search engine and information retrieval technologyarises at the historic moment.This paper proposes a workflow-based recommender system model on supplying properknowledge to proper members in collaborative team contexts rather than daily life scenarios,e.g., recommending commodities, films, news, etc. Within collaborative team contexts, moreinformation could be utilized by recommender systems than ordinary daily life contexts. Theworkflow in collaborative team contains information about relationships among members, rolesand tasks, which could be combined with collaborative filtering to obtain members’ demands forknowledge. In addition, the work schedule information contained in the workflow could also beemployed to determine the proper volume of knowledge that should be recommended to eachmember.In this paper we study the working process of the system based on the mechanism ofoperation recommended, and carried out a series of team cooperation experiment, theexperimental results verify the working process of the system based on the effectiveness of highefficiency and recommended. From this experiment, we could see the proposed CF based onworkflow outperforms the ordinary CF, especially the one considering relationships amongtasks. Those results reflect that the collaborative environment could supply more informationabout the implicative relationships among members so as to improve the CF efficiency. Itmeans the ‘sequential’ relationship has higher influence on corresponding members than‘subtype’ and ‘part of’ relationships. We also found that is the working experiences’ impact onthe recommendation volume control for different members.The experiment shows that the proposed workflowbased CF may be much more suitableto those teams or organizations with more potential and implicative collaborations amongmembers.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Retrieval machine
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