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- 13 creator celine-van-damme.
- 13 type InProceedings.
- 13 label "Approaches to Analyse Corporate Tags for Business Intelligence Purposes".
- 13 sameAs 13.
- 13 abstract "The information overload in business organizations hampers the information analysis process. Business intelligence tools can be used to analyse large amounts of information, however in most cases they only focus on structured information. More and more companies annotate tags to unstructured information to improve the information retrieval. We propose to exploit tags and tagging data to generate business intelligence. We believe that the analysis of unstructured information for business intelligence purposes can be reduced to analysing tags and tag data. In the paper, we outline the contribution that (1) tags and tag data can produce business intelligence from unstructured information provided that some prerequisites are taken into account, (2) suggest two step-by-step approaches of how existing mining and statistical techniques can be applied on tags and tagged data (3) by means of a tag data set from a European company, we provide preliminary evidence that the proposed approaches applied on corporate tags produce promising results.".
- 13 hasAuthorList authorList.
- 13 isPartOf proceedings.
- 13 keyword "Algorithms".
- 13 keyword "Business Intelligence".
- 13 keyword "Corporate Tags".
- 13 keyword "Unstructured Information".
- 13 title "Approaches to Analyse Corporate Tags for Business Intelligence Purposes".
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- 14 creator branimir-wetzstein.
- 14 creator carlos-pedrinaci.
- 14 creator dave-lambert.
- 14 creator luchesar-cekov.
- 14 creator marin-dimitrov.
- 14 creator tammo-van-lessen.
- 14 type InProceedings.
- 14 label "SENTINEL: A Semantic Business Process Monitoring Tool".
- 14 sameAs 14.
- 14 abstract "Business Activity Monitoring (BAM) aims to support the real-time analysis of business processes in order to improve the speed and effectiveness of business operations. Timely providing an integrated high-level view on the evolution and well-being of business activities within enterprises constitutes an obviously highly valuable analytical tool for monitoring, managing and hopefully enhancing businesses. However, the degree of automation currently achieved cannot support the level of reactivity and adaptation demanded by businesses. We argue that the fundamental problem is that moving between the business level and the IT level is hardly automated and suggest an extensive use of semantic technologies as a solution. In particular, we present SENTINEL a Semantic Business Process Monitoring tool that advances the state of the art in BAM by making an extensive use of semantic technologies in order to support the integration and derivation of business level knowledge out of low-level audit trails generated by IT systems.".
- 14 hasAuthorList authorList.
- 14 isPartOf proceedings.
- 14 keyword "Business Activity Monitoring".
- 14 keyword "Business Intelligence".
- 14 keyword "Ontology".
- 14 keyword "Semantic Business Process Management".
- 14 title "SENTINEL: A Semantic Business Process Monitoring Tool".
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- 2 creator adam-funk.
- 2 creator christian-leibold.
- 2 creator horacio-saggion.
- 2 creator kalina-bontcheva.
- 2 creator yaoyong-li.
- 2 type InProceedings.
- 2 label "Opinion Analysis for Business Intelligence".
- 2 sameAs 2.
- 2 abstract "More than ever before, business analysts have access to public forums in which opinions and sentiments about companies, products, and policies are expressed in unstructured form. Mining information from public sources is of great importance to many business intelligence applications such as credit rating or company reputation. We have implemented a supervised machine-learning system which uses linguistic information to classify text by rating (good or bad, for example, or 1 to 5 stars). In an evaluation we have obtained good results in comparison with the state-of-the-art in opinion mining. We are further developing the system to classify each text according to a "qualitative variable" category from an ontology specially developed for Business Intelligence (BI). This work will allow us to generate RDF statements to populate a knowledge base for BI.".
- 2 hasAuthorList authorList.
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- 2 keyword "Business Intelligence".
- 2 keyword "Opinion Analysis".
- 2 keyword "Sentiment Extraction".
- 2 title "Opinion Analysis for Business Intelligence".
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