Intellexer


intellexer.com (@intellexer) {related:}

Notes:

  • Categorizer
  • Clusterizer
  • Comparator
  • Desktop Applications
  • Intellexer API
  • Intellexer SDK
  • Language Recognizer
  • Linguistic Processor
  • Named Entity Recognizer
  • Natural Language Interface
  • Preformator
  • Question Comparison Tool
  • Question-Answering System
  • Related Facts
  • Sentiment Analyzer
  • SpellChecker
  • Summarizer

See also:

Automatic Summarization


Intellexer Question Answering. A Bondarionok, A Bobkov, L Sudanova, P Mazur… – TREC, 2007 – lucky-one.com The core of Intellexer QA system is a set of modules for natural language processing that perform classic steps of text analysis. The NLP module include: initial preformatting and format conversion (eg html to plain text) module, tokenizer, statistical part-of-speech … All 2 versions

Review of Proposed Architectures for Automated Text Summarization T Yedke, V Jain, RS Prasad – … of International Conference on Advances in …, 2012 – Springer … Table 1. Comparative Results of Subjective Evaluation Summarizer Precision Recall F-measure Copernic 0.8 0.775 0.786 Intellexer 0.825 0.7083 0.7559 MS-Word 0.5916 0.625 0.5913 … Summarizer Content Readability OR Copernic 9 8.5 8.5 Intellexer 9 8 8 MS-Word 6 6.5 6.5 … Related articles All 3 versions

The performance of BLMSumm: Distinct languages with antagonistic domains and varied compressions MA Oliveira, MVC Guelpeli – Information Science and …, 2012 – ieeexplore.ieee.org … From the information available online and after contacting the suppliers, we were unable to obtain specific details regarding the algorithm it uses. • Intellexer Summarizer Pro – is also a professional summarizer that can be used for texts in the English language. … Related articles All 4 versions

Automatic Text Document Summarization Based on Machine Learning G Silva, R Ferreira, RD Lins, L Cabral… – Proceedings of the …, 2015 – dl.acm.org … 2http://www.cs.waikato.ac.nz/ml/weka/ Figure 1: Selected Features Text Summarizer (OTS), Text Compactor (TC), Free Sum- marizer (FS), Smmry (SUMM), Web Summarizer (WEB), Intellexer Summarizer (INT)3, Compendium (COMP) [10]. …

A feasibility study for a mass-customization system RA Niemeijer, B de Vries – … Workshop on Design for Variety in …, 2007 – ds.arch.tue.nl … Specialized systems, called natural language processors, have been made solely to deal with this problem. Examples of NLP systems include the open source NLTK [27] and OpenNLP [28] and the commercial Intellexer SDK [29] and LingPipe [30]. … Cited by 3 Related articles All 2 versions

Convertor from Text to Poetry, Song or Music: Computer-assisted aesthetic enhancement of treaties, declarations and agreements A Judge – 2007 – laetusinpraesens.org Possibilities for computer-assisted systematic conversion of text into poetry, song or music. The focus is on the desirable options, the specific software challenges, and the useful applications associated with various stages of development. Emphasis is on the aesthetic enhancement …

Harvesting knowledge from computer mediated social networks OS Ogunseye, PK Adetiloye, SO Idowu, O Folorunso… – VINE, 2011 – emeraldinsight.com … To ensure comparison and for the sake of the prototype we used a commercial document Comparator API from intellexer semantic solutions. Developers can develop their own comparators, get open source comparators or use off? the?shelf comparator APIs. … Cited by 5 Related articles All 4 versions

The process of summarization in the pre-processing stage in order to improve measurement of texts when clustering MVC Guelpeli, ACB Garcia… – Internet Technology and …, 2011 – ieeexplore.ieee.org … For the summarization process in English, three summarizers were used, one professional and another literature, which is available in the web: Copernic and Intellexer Summarizer Pro are professional summarizers and their algorithms are considered black boxes. … Cited by 1 Related articles All 6 versions

The process of summarization in the pre-processing stage in order to improve measurement of texts when clustering AH Branco – addlabs.uff.br … For the summarization process in English, three summarizers were used, one professional and another literature, which is available in the web: Copernic and Intellexer Summarizer Pro are professional summarizers and their algorithms are considered black boxes. … Related articles

The Cassiopeia Model: A study with other algorithms for attribute selection in text clusterization. AH Branco – researchgate.net … As in all corpus simulations in Portuguese and English, three summarizers were used (Gist_Keyword, Gist_Intra and Supor) for the Portuguese language (Copernic, Intellexer and SweSum), for the English language, and four compressions (50%, 70%, 80% and 90%). … Related articles All 5 versions

A framework for text summarization in mobile web browsers J Bose, DK Puthenveettil, SG Kasi… – … (ICCIC), 2013 IEEE …, 2013 – ieeexplore.ieee.org … 22] Setooz Summarizer http://wc41.setooz.com/summarizer [23] Lexalytics http://www.lexalytics. com/web-demo [24] Sensebot semantic search engine http://www.sensebot.net/ [25] Hakia Summarizer http://company.hakia.com/syndication.html [26] IES Intellexer summarizer http … Related articles All 3 versions

The Cassiopeia Model: Using summarization and clusterization for semantic knowledge management MVC Guelpeli, CB Garcia… – Applications of Digital …, 2011 – ieeexplore.ieee.org … For the summarization process in English, three summarizers were used, one professional and another literature, which is available in the web: Copernic and Intellexer Summarizer Pro are professional summarizers and their algorithms are considered black boxes. … Related articles All 2 versions

The Cassiopeia Model AH Branco – addlabs.uff.br … For the summarization process in English, three summarizers were used, one professional and another literature, which is available in the web: Copernic and Intellexer Summarizer Pro are professional summarizers and their algorithms are considered black boxes. … Related articles All 5 versions

An Introduction to Text Mining CAS 2008 Predictive Modeling Seminar L Francis – 2008 – casualtyactuaries.com Page 1. An Introduction to Text Mining CAS 2008 Predictive Modeling Seminar Prepared by Louise Francis Francis Analytics and Actuarial Data Mining, Inc. Oct, 2008 Louise_francis@msn.com www.data-mines.com Page 2. Objectives • Present a new data mining technology … Related articles All 14 versions

CAS 2008 Predictive Modeling Seminar L Francis – 2008 – data-mines.com Page 1. Text Mining on Unstructured Data CAS 2008 Predictive Modeling Seminar Prepared by Louise Francis Francis Analytics and Actuarial Data Mining, Inc. Oct, 2008 Louise_francis@msn.com www.data-mines.com Page 2. Objectives … Related articles All 3 versions

A Text Summarization Using Modern Features And Fuzzy Logic MBD Abhiman, PP Rokade – 2015 – ijcsmc.com … Performance Analysis of Modern featured base text summarization (MFBTS) with existing Tools. Features Extraction Copernic Summarizer (Feb 2003) Intellexer MS word Fuzzy Logic (2009) Developed System(Considering 14 features for extraction) Alpha Numeric Sentences …

Enhancing extractive summarization with automatic post-processing SMSB Silveira – 2015 – repositorio.ul.pt Page 1. UNIVERSIDADE DE LISBOA FACULDADE DE CIÊNCIAS DEPARTAMENTO DE INFORMÁTICA ENHANCING EXTRACTIVE SUMMARIZATION WITH AUTOMATIC POST-PROCESSING Sara Maria da Silveira Botelho da Silveira Doutoramento em Informática …

State of the Art in Cross-Media Analysis, Metadata Publishing, Querying and Recommendations TK Stegmaier, G Miller – 2014 – mico-project.eu … Task Common techniques Software tools Document categorization SVM, Naive Bayes, Kernel meth- ods Intellexer Categorizer, NetOwl Doc- Matcher Authorship attribution SVM, Naive Bayes, Weighted au- tomata Signature, JGAAP … Related articles All 2 versions

Automatic genre recognition and adaptive text summarization VA Yatsko, MS Starikov, AV Butakov – Automatic Documentation and …, 2010 – Springer Page 1. ISSN 0005 1055, Automatic Documentation and Mathematical Linguistics, 2010, Vol. 44, No. 3, pp. 111–120. © Allerton Press, Inc., 2010. Original Russian Text © VA Yatsko, MS Starikov, AV Butakov, 2010, published … Cited by 10 Related articles All 6 versions

State of the Art in Cross-Media Analysis, Metadata Publishing, Querying and Recommendations P Aichroth, J Björklund, F Stegmaier, T Kurz, G Miller – 2015 – mico-project.eu … Task Common techniques Software tools Document categorization SVM, Naive Bayes, Kernel meth- ods Intellexer Categorizer, NetOwl Doc- Matcher Authorship attribution SVM, Naive Bayes, Weighted au- tomata Signature, JGAAP …

[BOOK] Automatic Text Summarization JM Torres-Moreno – 2014 – books.google.com Page 1. Automatic Text Summarization Page 2. Page 3. Series Editor Jean-Charles Pomerol Automatic Text Summarization Juan-Manuel Torres-Moreno Page 4. First published 2014 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc. … Cited by 3 Related articles All 4 versions

Privacy-preserving document similarity detection K Khelik – 2011 – brage.bibsys.no Page 1. 1 This Master’s Thesis is carried out as a part of the education at the University of Agder and is therefore approved as a part of this education University of Agder, 2011 Faculty of Engineering and Science Department of ICT … Related articles

Automatic documents summarization using ontology based methodologies A Bawakid – 2011 – etheses.bham.ac.uk Page 1. UNIVERSITY OF BIRMINGHAM Automatic Documents Summarization Using Ontology based Methodologies Abdullah Bawakid Thesis submitted for the degree of Doctor of Philosophy School of Electronic, Electrical … Cited by 2 Related articles All 5 versions