about
[Analysis of health terminologies for use as ontologies in healthcare information systems].A knowledge based method for the medical question answering problem.A novel concept-level approach for ultra-concise opinion summarizationExtractive Text Summarization: Can We Use the Same Techniques for Any Text?A Comparative Study of the Impact of Statistical and Semantic Features in the Framework of Extractive Text SummarizationStudying the Influence of Semantic Constraints in AVEImproving Question Answering Tasks by Textual Entailment RecognitionTE4AV: Textual Entailment for Answer ValidationAn Algorithm for Anaphora Resolution in Spanish TextsProcessing of Spanish Definite DescriptionsAnalysing and evaluating the task of automatic tweet generation: Knowledge to businessIncremental and Adaptive Software Systems Development of Natural Language ApplicationsTowards the Design of a Chemical Textile OntologyCOMPENDIUM: A text summarization system for generating abstracts of research papersTowards automatic tweet generation: A comparative study from the text summarization perspective in the journalism genreTackling redundancy in text summarization through different levels of language analysisApplication of Text Summarization techniques to the Geographical Information Retrieval taskTowards a unified framework for opinion retrieval, mining and summarizationCan Text Summaries Help Predict Ratings? A Case Study of Movie ReviewsText summarisation in progress: a literature reviewText summarization contribution to semantic question answering: New approaches for finding answers on the webCOMPENDIUM: A Text Summarization System for Generating Abstracts of Research Papers
P50
Q38511812-C24A1B59-C7ED-403E-81EA-DB564A085EA0Q48694085-90B483DF-511F-49FC-9EC2-C747EC6601E4Q57712945-10D86661-6E1B-4B8D-AD0D-9B08C67BAA23Q57712948-6BF05181-F3F3-423C-9B3E-0521D8BC5583Q57712949-DB0DD2F2-5C82-4DC7-A154-701B6D179D99Q57712976-3F465EEE-6835-451D-BAA4-D015A4125E87Q57712981-3D78AF31-AA9C-46B7-9B84-BABB3495A0E9Q57712989-0D09BD98-A37C-4123-8142-3A745236730EQ57713010-DBCF766F-DC08-4780-AC08-1B1374240C68Q57713011-31A99766-AE77-40EE-8BC3-6A264508BAAAQ57727025-BEEA17D2-2714-4E39-A694-8227B15EC049Q57727045-456091BC-A0A0-4B91-AD11-3F2BC507DC17Q57727048-7A3D129A-E6AD-4C49-B14B-3957EAB8CEFBQ57727050-4E42B7A2-E629-48BB-9570-59B9980D9404Q57727053-5859FDED-3357-4348-BE6F-72CD9161FCD5Q57727055-20379CF2-D5C0-4B31-B530-D4655D6545B1Q57727057-B6434BC7-CE1B-41DB-AF73-EB1623BCE4FEQ57727067-5D9446C1-FC48-4063-90D9-EA522E427115Q57727069-D6056D8E-3496-4372-A708-E5E6880D6BFDQ57727073-007D52D7-3307-47F7-A46A-D1388AC1425DQ57727076-7C2F2F76-FBFE-4CB4-BEC2-4A0789F4C213Q57727077-7BC230D8-2BC0-4132-B444-55D064929CB0
P50
description
onderzoeker
@nl
researcher
@en
հետազոտող
@hy
name
Manuel Palomar
@ast
Manuel Palomar
@en
Manuel Palomar
@es
Manuel Palomar
@nl
type
label
Manuel Palomar
@ast
Manuel Palomar
@en
Manuel Palomar
@es
Manuel Palomar
@nl
prefLabel
Manuel Palomar
@ast
Manuel Palomar
@en
Manuel Palomar
@es
Manuel Palomar
@nl
P106
P2456
p/ManuelPalomar
P31
P496
0000-0002-1441-7865