D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 34 Citations 5,502 251 World Ranking 8075 National Ranking 133

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Programming language

His primary areas of investigation include Information retrieval, Artificial intelligence, Natural language processing, Sentiment analysis and Semantic Web. His Information retrieval study combines topics from a wide range of disciplines, such as Text mining, Event and Semantics. His research integrates issues of Context, Contrast and Data mining in his study of Artificial intelligence.

The Sentiment analysis study combines topics in areas such as Sentence, Structure, Rhetorical question and Lexicon. His Semantic Web research is within the category of World Wide Web. His research investigates the link between Semantic Web Stack and topics such as Social Semantic Web that cross with problems in Semantic search, Semantic computing and Semantic grid.

His most cited work include:

  • Survey on Aspect-Level Sentiment Analysis (287 citations)
  • Exploiting emoticons in sentiment analysis (145 citations)
  • Engineering semantic web information systems in Hera (126 citations)

What are the main themes of his work throughout his whole career to date?

His scientific interests lie mostly in Information retrieval, Artificial intelligence, Natural language processing, Semantic Web and World Wide Web. Flavius Frasincar interconnects Product, Semantics and Personalization in the investigation of issues within Information retrieval. Flavius Frasincar has researched Artificial intelligence in several fields, including Structure and Machine learning.

His Natural language processing study combines topics in areas such as Context, Word and Web Ontology Language. His Semantic Web research includes themes of Decision support system and Knowledge base. His studies deal with areas such as Negation, Lexicon, Text mining, SemEval and Focus as well as Sentiment analysis.

He most often published in these fields:

  • Information retrieval (39.69%)
  • Artificial intelligence (28.79%)
  • Natural language processing (23.74%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (28.79%)
  • Sentiment analysis (20.62%)
  • Natural language processing (23.74%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Artificial intelligence, Sentiment analysis, Natural language processing, Ontology and Support vector machine. His work deals with themes such as Machine learning and Recommender system, which intersect with Artificial intelligence. His study in Sentiment analysis is interdisciplinary in nature, drawing from both Hybrid approach, Service, Text mining, Structure and Social media.

His research in Natural language processing tackles topics such as Word which are related to areas like Negation, Finance and Lexicon. His Ontology study introduces a deeper knowledge of Information retrieval. His Information retrieval research is multidisciplinary, relying on both Semantics, Software and Personalization.

Between 2017 and 2021, his most popular works were:

  • Supervised and Unsupervised Aspect Category Detection for Sentiment Analysis with Co-occurrence Data (54 citations)
  • Ontology-Driven Sentiment Analysis of Product and Service Aspects (17 citations)
  • A Hybrid Approach for Aspect-Based Sentiment Analysis Using a Lexicalized Domain Ontology and Attentional Neural Models (16 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Programming language

Flavius Frasincar focuses on Sentiment analysis, Ontology, Artificial intelligence, Natural language processing and Information retrieval. His research investigates the connection between Sentiment analysis and topics such as Service that intersect with issues in Product, Product, Data mining, Co-occurrence and Text mining. His Artificial intelligence study which covers Structure that intersects with Context.

His Natural language processing research integrates issues from Association rule learning, Contrast and Word. His Information retrieval research includes themes of Semantics, Semantic lexicon and Extension. Flavius Frasincar has included themes like Semantic Web, Concept Relationship and Personalization in his Semantics study.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Survey on Aspect-Level Sentiment Analysis

Kim Schouten;Flavius Frasincar.
IEEE Transactions on Knowledge and Data Engineering (2016)

579 Citations

Exploiting emoticons in sentiment analysis

Alexander Hogenboom;Daniella Bal;Flavius Frasincar;Malissa Bal.
acm symposium on applied computing (2013)

295 Citations

Ontology-based news recommendation

Wouter IJntema;Frank Goossen;Flavius Frasincar;Frederik Hogenboom.
edbt icdt workshops (2010)

188 Citations

Engineering semantic web information systems in Hera

Richard Vdovjak;Flavius Frasincar;Geert-Jan Houben;Peter Barna.
Journal of Web Engineering (2003)

182 Citations

An overview of event extraction from text

FP Hogenboom;F Flavius Frasincar;U Uzay Kaymak;de Fmg Jong.
conference; ISWC 2011; 2011-10-23; 2011-10-23 (2011)

166 Citations

Polarity analysis of texts using discourse structure

Bas Heerschop;Frank Goossen;Alexander Hogenboom;Flavius Frasincar.
conference on information and knowledge management (2011)

162 Citations

A Survey of event extraction methods from text for decision support systems

Frederik Hogenboom;Flavius Frasincar;Uzay Kaymak;Franciska de Jong.
decision support systems (2016)

126 Citations

Supervised and Unsupervised Aspect Category Detection for Sentiment Analysis with Co-occurrence Data

Kim Schouten;Onne van der Weijde;Flavius Frasincar;Rommert Dekker.
(2018)

115 Citations

Hera: development of semantic web information systems

Geert-Jan Houben;Peter Barna;Flavius Frasincar;Richard Vdovjak.
international conference on web engineering (2003)

105 Citations

Domain taxonomy learning from text: The subsumption method versus hierarchical clustering

Jeroen De Knijff;Flavius Frasincar;Frederik Hogenboom.
data and knowledge engineering (2013)

104 Citations

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