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124
Discovering Process in Curriculum Data to Provide Recommendation
"... ABSTRACT Process mining is an emerging technique that can discover the real sequence of various activities from an event log, compare different processes and ultimately find the bottleneck of an existing process and hence improve it. Curriculum data is the history of the courses effectively taken b ..."
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ABSTRACT Process mining is an emerging technique that can discover the real sequence of various activities from an event log, compare different processes and ultimately find the bottleneck of an existing process and hence improve it. Curriculum data is the history of the courses effectively taken
Recommended Citation
, 2007
"... Operational risk assessment of chemical industries by exploiting accident databases ..."
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Operational risk assessment of chemical industries by exploiting accident databases
Comparing two Recommender Algorithms with the Help Of Recommendations by Peers
- IN PROCEEDINGS OF THE 4TH INTERNATIONAL WORKSHOP ON MINING WEB DATA FOR DISCOVERING USAGE PATTERNS AND PROFILES
, 2003
"... Since more and more Web sites, especially sites of retailers, offer automatic recommendation services using Web usage mining, evaluation of recommender algorithms has become increasingly important. In this paper we present a framework for the evaluation of different aspects of recommender systems ba ..."
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Cited by 2 (0 self)
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based on the process of discovering knowledge in databases introduced by Fayyad et al. and we summarize research already done in this area. One aspect identified in the presented evaluation framework is widely neglected when dealing with recommender algorithms. This aspect is to evaluate how useful
Evaluation of Recommender Algorithms for an Internet Information Broker Based on Simple . . .
- PROCEEDINGS OF FOURTH WEBKDD WORKSHOP: WEB MINING FOR USAGE PATTERNS & USER PROFILES
, 2002
"... Association rules are a widely used technique to generate recommendations in commercial and research recommender systems. Since more and more Web sites, especially of retailers, offer automatic recommender services using Web usage mining, evaluation of recommender algorithms becomes increasingly imp ..."
Abstract
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Cited by 13 (0 self)
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important. In this paper we first present a framework for the evaluation of different aspects of recommender systems based on the process of discovering knowledge in databases of Fayyad et al. and then we focus on the comparison of the performance of two recommender algorithms based on frequent itemsets
Intelligent Data Mining
"... ii One of the most important challenges facing us today is to personalize services based on user preferences. In order to achieve this objective, the design of Recommender Systems (RSs), which are systems designed to aid the users through different decision-making processes by providing recommendati ..."
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ii One of the most important challenges facing us today is to personalize services based on user preferences. In order to achieve this objective, the design of Recommender Systems (RSs), which are systems designed to aid the users through different decision-making processes by providing
Digital Object Identifier (DOI):
"... Cell balance equation for chemotactic bacteria with a biphasic tumbling frequency ..."
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Cell balance equation for chemotactic bacteria with a biphasic tumbling frequency
RoK: Roll-Up with the K-means Clustering Method for Recommending OLAP Queries
"... Abstract. Dimension hierarchies represent a substantial part of the data warehouse model. Indeed they allow decision makers to examine data at different levels of detail with On-Line Analytical Processing (OLAP) operators such as drill-down and roll-up. The granularity levels which compose a dimensi ..."
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Abstract. Dimension hierarchies represent a substantial part of the data warehouse model. Indeed they allow decision makers to examine data at different levels of detail with On-Line Analytical Processing (OLAP) operators such as drill-down and roll-up. The granularity levels which compose a
Impact of different pre-processing tasks on effective identification of users’ behavioral patterns in web-based educational system
- Procedia Computer Science
"... Abstract Analyzing the unique types of data that come from educational systems can help find the most effective structure of the elearning courses, optimize the learning content, recommend the most suitable learning path based on student's behavior, or provide more personalized environment. We ..."
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Cited by 2 (1 self)
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logs of the web-based educational system and pre-processed in different ways: data with identified users' sessions and data with the reconstructed path among course activities. We try to assess the impact of these advanced techniques of data pre-processing on the quantity and quality
Risk-Hedged Venture Capital Investment Recommendation
"... With the increasing accessibility of transactional data in venture finance, venture capital firms (VCs) face great chal-lenges in developing quantitative tools to identify new in-vestment opportunities. Recommendation techniques have the possibility of helping VCs making data-driven invest-ment deci ..."
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decisions by providing an automatic screening process of a large number of startups across different domains on the basis of their past investment data. A previous study has shown the potential advantage of using collaborative fil-tering to catch and predict the VCs ’ investment behaviours [17]. However
IOS Press Semantic Enrichment for Recommendation of Primary Studies in a Systematic Literature Review
"... Abstract. A Systematic Literature Review (SLR) identifies, evaluates and synthesizes the literature available for a given topic. This generally requires a significant human workload and has subjectivity bias that could affect the results of such a review. Automated document classification can be a v ..."
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valuable tool for recommending the selection of primary studies. In this paper, we propose an automated pre-selection approach based on text mining and semantic enrichment techniques. Each document candidate is firstly processed by a named entity extractor. The DBpedia URIs coming from the entity linking
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