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Clustering Algorithms in Hybrid Recommender System on MovieLens Data

100%

Kuzelewska U.

Studies in Logic, Grammar and Rhetoric

2014

vol. 37

issue 1

125-139

Decisions are taken by humans very often during professional as well as leisure activities. It is particularly evident during surfing the Internet: selecting web sites to explore, choosing needed information in search engine results or deciding which product to buy in an on-line store. Recommender systems are electronic applications, the aim of which is to support humans in this decision making process. They are widely used in many applications: adaptive WWW servers, e-learning, music and video preferences, internet stores etc. In on-line solutions, such as e-shops or libraries, the aim of recommendations is to show customers the products which they are probably interested in. As input data the following are taken: shopping basket archives, ratings of the products or servers log files. The article presents a solution of recommender system which helps users to select an interesting product. The system analyses data from other customers' ratings of the products. It uses clustering methods to find similarities among the users and proposed techniques to identify users' profiles. The system was implemented in Apache Mahout environment and tested on a movie database. Selected similarity measures are based on: Euclidean distance, cosine as well as correlation coefficient and loglikehood function.

The Architecture of the Intelligent Case-Based Reasoning Recommender System (CBR RS) Recommending Preventive/Corrective Procedures in the Occupational Health and Safety Management System in an Enterprise

63%

Andreasik J.

Barometr Regionalny. Analizy i prognozy

2017

issue 3(49)

109-124

The paper presents the original architecture of the system recommending preventive/corrective procedures in the occupational health and safety management system in an enterprise: ComplianceOHS-CBR. The system consists of four modules: Module A — an ontology of the workplace OHS profile, Module B — an ontology of preventive/corrective procedure indexation OPCPI, Module C — a recording system of the monitoring process of non-compliance with the requirements of OHS, Module D — a recommending engine consistent with the CBR methodology. The essence of the approach presented in this paper is integration of the monitoring system of the analysis process of non-compliance with the requirements of OHS at the workplace (the ADONIS system was used) with the case-based reasoning process (CBR). The integration platform consists of two ontologies: an ontology of profile compliance with the workplace OHS requirements (OP-OHS) and an ontology of preventive/corrective procedure indexation (OPCPI). Both of the ontologies are presented in the Protege 5 OWL editor. Inference engines are alternatively, according to the CBR methodology, myCBR and jCOLLIBRI.

W pracy przedstawiono oryginalną architekturę systemu rekomendującego procedury zapobiegawczo-korygujące w systemie BHP przedsiębiorstwa: Compliance OHS-CBR. System składa się z czterech modułów: moduł A: ontologia profilu BHP stanowiska pracy, moduł B: ontologia indeksacji procedur zapobiegawczo-korygujących OIP-ZK, moduł C: system ewidencjonowania procesu monitorowania niezgodności z wymaganiami BHP, moduł D: silnik wydawania rekomendacji w metodologii CBR. Istotą podejścia prezentowanego w niniejszej pracy jest integracja systemu monitorowania procesu analizy niezgodności z wymaganiami BHP na stanowiskach pracy (zastosowano oprogramowanie ADONIS) z systemem wnioskowania z bazy przypadków CBR. Platformą integracji są dwie ontologie: ontologia profilu zgodności z wymaganiami BHP na stanowisku pracy (OP-BHP) oraz ontologia indeksacji procedur zapobiegawczo--korygujących OIP-ZK. Obydwie ontologie przedstawiono w edytorze Protege 5 języka OWL. Silnikami wnioskującymi zgodnie z metodologią CBR są alternatywnie: myCBR oraz jCOLLIBRI.

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1 Barometr Regionalny. Analizy i prognozy

1 Studies in Logic, Grammar and Rhetoric

1 Andreasik J.

1 Kuzelewska U.

1 2017

1 2014

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Clustering Algorithms in Hybrid Recommender System on MovieLens Data

The Architecture of the Intelligent Case-Based Reasoning Recommender System (CBR RS) Recommending Preventive/Corrective Procedures in the Occupational Health and Safety Management System in an Enterprise