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ORCID: https://orcid.org/0000-0003-2003-5385, Goñi Menoyo, José Miguel
ORCID: https://orcid.org/0000-0001-8922-5529 and González Cristóbal, José Carlos
ORCID: https://orcid.org/0000-0002-1461-2695
(2006).
Report of MIRACLE team for Geographical IR in CLEF 2006.
En: "7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006", 20/09/2006-22/09/2006, Alicante, España. ISBN 2-912335-23-x.
| Título: | Report of MIRACLE team for Geographical IR in CLEF 2006 |
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| Autor/es: |
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| Tipo de Documento: | Ponencia en Congreso o Jornada (Artículo) |
| Título del Evento: | 7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006 |
| Fechas del Evento: | 20/09/2006-22/09/2006 |
| Lugar del Evento: | Alicante, España |
| Título del Libro: | Working Notes for the CLEF 2006 Workshop |
| Fecha: | 2006 |
| ISBN: | 2-912335-23-x |
| Materias: | |
| ODS: | |
| Palabras Clave Informales: | Geographical IR, geographic entity recognition, spatial retrieval, gazetteer, linguistic engineering, information retrieval, trie indexing |
| Escuela: | E.U.I.T. Telecomunicación (UPM) [antigua denominación] |
| Departamento: | Ingeniería y Arquitecturas Telemáticas [hasta 2014] |
| Grupo Investigación UPM: | Grupo de Sistemas Inteligentes |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
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The main objective of the designed experiments is testing the effects of geographical information retrieval from documents that contain geographical tags. In the designed experiments we try to isolate geographical retrieval from textual retrieval replacing all geo-entity textual references from topics with associated tags and splitting the retrieval process in two phases: textual retrieval from the textual part of the topic without geo-entity references and geographical retrieval from the tagged text generated by the topic tagger. Textual and geographical results are combined applying different techniques: union, intersection, difference, and external join based. Our geographic information retrieval system consists of a set of basics components organized in two categories: (i) linguistic tools oriented to textual analysis and retrieval and (ii) resources and tools oriented to geographical analysis. These tools are combined to carry out the different phases of the system: (i) documents and topics analysis, (ii) relevant documents retrieval and (iii) result combination. If we compare the results achieved to the last campaign’s results, we can assert that mean average precision gets worse when the textual geo-entity references are replaced with geographical tags. Part of this worsening is due to our experiments return cero pertinent documents if no documents satisfy de geographical sub-query. But if we only analyze the results of queries that satisfied both textual and geographical terms, we observe that the designed experiments recover pertinent documents quickly, improving R-Precision values. We conclude that the developed geographical information retrieval system is very sensible to textual georeference and therefore it is necessary to improve the name entity recognition module.
| ID de Registro: | 4690 |
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| Identificador DC: | https://oa.upm.es/4690/ |
| Identificador OAI: | oai:oa.upm.es:4690 |
| URL Oficial: | http://ims-sites.dei.unipd.it/documents/71612/8636... |
| Depositado por: | Memoria Investigacion |
| Depositado el: | 22 Oct 2010 11:07 |
| Ultima Modificación: | 20 Abr 2016 13:48 |
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