626 research outputs found

    Exploiting Synergy Between Ontologies and Recommender Systems

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    Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations. Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain. This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured

    Exploiting synergy between ontologies and recommender systems

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    Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations.Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain. This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured

    Virtual Machines Embedding for Cloud PON AWGR and Server Based Data Centres

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    In this study, we investigate the embedding of various cloud applications in PON AWGR and Server Based Data Centres

    Effect of Exchange Rate Fluctuation on the Financial Performance Evaluation of Multinational Companies in Nigeria

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    The research work examined the effect of exchange rate fluctuation on performance evaluations of multinational companies in Nigeria. The objective of the study was to examine how foreign exchange affects financial performance of multinational companies in Nigeria. This Study is based on the transaction cost theory, liquidity theory, inflation theory and managerial theory of firm performance. Secondary data source was explored in presenting the facts of the situation. The secondary data were obtained from relevant literatures, Central Bank of Nigeria Statistical Bulletin and annual report of selected multinational companies in Nigeria. Data were tested using the Ordinary Least Square Linear Regression model. Findings show that exchange rate fluctuation has significant effect on performance of multinational companies in Nigeria. As a result, the study concluded that exchange rate instability affects the operations of companies in Nigeria vis-à-vis international trade with other countries of the world. It was recommended that, Multinational Companies should develop a robust foreign exchange risk management framework which will clearly show its currency risk assessment procedures and implementation of foreign exchange risk management strategy. These strategies should be monitored and adjusted regularly. Keywords: Exchange rate, Financial Performance, Inflation rate, Interest rate, Multinationals companies, Return on Assets. DOI: 10.7176/RJFA/10-16-03 Publication date: August 31st 201

    Using Protege for automatic ontology instantiation

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    This paper gives an overview on the use of Protégé in the Artequakt system, which integrated Protégé with a set of natural language tools to automatically extract knowledge about artists from web documents and instantiate a given ontology. Protégé was also linked to structured templates that generate documents from the knowledge fragments it maintains

    Web based knowledge extraction and consolidation for automatic ontology instantiation

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    The Web is probably the largest and richest information repository available today. Search engines are the common access routes to this valuable source. However, the role of these search engines is often limited to the retrieval of lists of potentially relevant documents. The burden of analysing the returned documents and identifying the knowledge of interest is therefore left to the user. The Artequakt system aims to deploy natural language tools to automatically ex-tract and consolidate knowledge from web documents and instantiate a given ontology, which dictates the type and form of knowledge to extract. Artequakt focuses on the domain of artists, and uses the harvested knowledge to gen-erate tailored biographies. This paper describes the latest developments of the system and discusses the problem of knowledge consolidation

    Automatic extraction of knowledge from web documents

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    A large amount of digital information available is written as text documents in the form of web pages, reports, papers, emails, etc. Extracting the knowledge of interest from such documents from multiple sources in a timely fashion is therefore crucial. This paper provides an update on the Artequakt system which uses natural language tools to automatically extract knowledge about artists from multiple documents based on a predefined ontology. The ontology represents the type and form of knowledge to extract. This knowledge is then used to generate tailored biographies. The information extraction process of Artequakt is detailed and evaluated in this paper

    Generating adaptive hypertext content from the semantic web

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    Accessing and extracting knowledge from online documents is crucial for therealisation of the Semantic Web and the provision of advanced knowledge services. The Artequakt project is an ongoing investigation tackling these issues to facilitate the creation of tailored biographies from information harvested from the web. In this paper we will present the methods we currently use to model, consolidate and store knowledge extracted from the web so that it can be re-purposed as adaptive content. We look at how Semantic Web technology could be used within this process and also how such techniques might be used to provide content to be published via the Semantic Web
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