David E. Losada
David E. Losada

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Average citations per article3.07
Citation Count126
Publication count41
Publication years1999-2016
Available for download18
Average downloads per article263.56
Downloads (cumulative)4,744
Downloads (12 Months)202
Downloads (6 Weeks)16
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41 results found Export Results: bibtexendnoteacmrefcsv

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1 published by ACM
June 2016 CERI '16: Proceedings of the 4th Spanish Conference on Information Retrieval
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 2,   Downloads (12 Months): 14,   Downloads (Overall): 30

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Automatic Text Summarisation is an essential technology to cope with the overwhelming amount of documents that are daily generated. Given an information source, such as a webpage or a news article, text summarisation consists of extracting content from it and present it in a condensed form for human consumption. Summaries ...
Keywords: LIWC, Summarisation, psychological features, PSO

2 published by ACM
April 2016 SAC '16: Proceedings of the 31st Annual ACM Symposium on Applied Computing
Publisher: ACM
Bibliometrics:
Citation Count: 6
Downloads (6 Weeks): 3,   Downloads (12 Months): 34,   Downloads (Overall): 50

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Evaluation is crucial in Information Retrieval. The Cranfield paradigm allows reproducible system evaluation by fostering the construction of standard and reusable benchmarks. Each benchmark or test collection comprises a set of queries, a collection of documents and a set of relevance judgements. Relevance judgements are often done by humans and ...
Keywords: information retrieval, multi-armed bandits, pooling

3
May 2015 Information Fusion: Volume 23 Issue C, May 2015
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 2

In the blogosphere, different actors express their opinions about multiple topics. Users, companies or editors socially interact by commenting, recommending and linking blogs and posts. These social media contents are increasingly growing. As a matter of fact, the size of the blogosphere is estimated to double every six months. In ...
Keywords: Blog distillation, Information retrieval, Differential evolution, Line search, Particle swarm optimisation

4
November 2014 Data & Knowledge Engineering: Volume 94 Issue PB, November 2014
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 0

Sentiment analysis tools often rely on counts of sentiment-carrying words, ignoring structural aspects of content. Natural Language Processing has been fruitfully exploited in text mining, but advanced discourse processing is still nonpervasive for mining opinions. Some studies, however, extracted opinions based on the discursive role of text segments. The merits ...
Keywords: Information Retrieval, Natural Language Processing, Text mining, Rhetorical Structure Theory, Sentiment analysis

5
October 2013 IRFC 2013: Proceedings of the 6th Information Retrieval Facility Conference on Multidisciplinary Information Retrieval - Volume 8201
Publisher: Springer-Verlag New York, Inc.
Bibliometrics:
Citation Count: 0

In recent years, several machine learning methods have been proposed to detect subjective opinionated expressions within on-line documents. This task is important in many Opinion Mining and Sentiment Analysis applications. However, the opinion extraction process is often done with rough content-based features. In this paper, we study the role of ...
Keywords: Subjectivity Classification, Machine Learning, Rhetorical Structure Theory, Sentiment Analysis, Opinion Mining, Information Retrieval

6 published by ACM
December 2012 ACM SIGIR Forum: Volume 46 Issue 2, December 2012
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 1,   Downloads (12 Months): 2,   Downloads (Overall): 72

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7 published by ACM
October 2011 SMUC '11: Proceedings of the 3rd international workshop on Search and mining user-generated contents
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 1,   Downloads (12 Months): 20,   Downloads (Overall): 165

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This talk is focused on a key task in the area of Opinion Mining and Sentiment Analysis: polarity classification of social media documents (e.g. blog posts). Estimating polarity is much more demanding than estimating topicality. As a matter of fact, the effectiveness of polarity classification is still modest and does ...
Keywords: polarity, social media, opinion mining, sentiment analysis

8 published by ACM
October 2011 CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge management
Publisher: ACM
Bibliometrics:
Citation Count: 6
Downloads (6 Weeks): 0,   Downloads (12 Months): 6,   Downloads (Overall): 239

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One of the core tasks in Opinion Mining consists of estimating the polarity of the opinionated documents found. In some scenarios (e.g. blogs), this estimation is severely affected by sentences that are off-topic or that simply do not express any opinion. In fact, the key sentiments in a blog post ...
Keywords: blog retrieval, polarity estimation, efficiency, opinion mining, sentence retrieval

9
August 2011 Information Retrieval: Volume 14 Issue 4, August 2011
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 8

Employing effective methods of sentence retrieval is essential for many tasks in Information Retrieval, such as summarization, novelty detection and question answering. The best performing sentence retrieval techniques attempt to perform matching directly between the sentences and the query. However, in this paper, we posit that the local context of ...
Keywords: Language models, Sentence retrieval, Information retrieval, Context

10 published by ACM
July 2011 SIGIR '11: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Publisher: ACM
Bibliometrics:
Citation Count: 2
Downloads (6 Weeks): 0,   Downloads (12 Months): 13,   Downloads (Overall): 355

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In this paper we perform a lab-based user study (n=21) of email re-finding behaviour, examining how the characteristics of submitted queries change in different situations. A number of logistic regression models are developed on the query data to explore the relationship between user- and contextual- variables and query characteristics including ...
Keywords: evaluation, personal search, user study, email re-finding

11
October 2010 Information Retrieval: Volume 13 Issue 5, October 2010
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 7

The retrieval of sentences that are relevant to a given information need is a challenging passage retrieval task. In this context, the well-known vocabulary mismatch problem arises severely because of the fine granularity of the task. Short queries, which are usually the rule rather than the exception, aggravate the problem. ...
Keywords: Information retrieval, Query expansion, Sentence retrieval

12 published by ACM
July 2010 SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 1,   Downloads (12 Months): 15,   Downloads (Overall): 215

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The retrieval of sentences is a core task within Information Retrieval. In this poster we employ a Language Model that incorporates a prior which encodes the importance of sentences within the retrieval model. Then, in a set of comprehensive experiments using the TREC Novelty Tracks, we show that including this ...
Keywords: language models, sentence retrieval

13 published by ACM
July 2010 SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 0,   Downloads (12 Months): 9,   Downloads (Overall): 218

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Novelty detection is a difficult task, particularly at sentence level. Most of the approaches proposed in the past consist of re-ordering all sentences following their novelty scores. However, this re-ordering has usually little value. In fact, a naive baseline with no novelty detection capabilities yields often better performance than any ...
Keywords: novelty detection, sentence clustering

14 published by ACM
November 2009 CIKM '09: Proceedings of the 18th ACM conference on Information and knowledge management
Publisher: ACM
Bibliometrics:
Citation Count: 3
Downloads (6 Weeks): 1,   Downloads (12 Months): 14,   Downloads (Overall): 238

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Opinion mining has become recently a major research topic. A wide range of techniques have been proposed to enable opinion-oriented information seeking systems. However, little is known about the ability of opinion-related information to improve regular retrieval tasks. Our hypothesis is that standard retrieval methods might benefit from the inclusion ...
Keywords: opinion mining, sentence retrieval

15
September 2009 CLEF'09: Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

In this paper we describe our participation in CLEF-IP 2009 (prior art search task). This was the first year of the task and we focused on how to build effectively a prior art query from a patent. Basically, we implemented simple strategies to extract terms from some textual fields of ...

16 published by ACM
July 2009 SIGIR '09: Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 0,   Downloads (12 Months): 8,   Downloads (Overall): 208

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The inclusion of document length factors has been a major topic in the development of retrieval models. We believe that current models can be further improved by more refined estimations of the document's scope. In this poster we present a new document length prior that uses the size of the ...
Keywords: language models, document priors, compression, document length

17
June 2009 IWINAC '09: Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part II: Bioinspired Applications in Artificial and Natural Computation
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 1

This paper is concerned with automatic classification of texts in a medical domain. The process consists in classifying reports of medical discharges into classes defined by the <em>CIE-9-MC</em> codes. We will assign <em>CIE-9-MC</em> codes to reports using either a <em>knn</em> model or support vector machines. One of the added values ...

18
June 2009 International Journal of Intelligent Systems - Fuzzy Bags, Cardinality, and Quantification: Volume 24 Issue 6, June 2009
Publisher: John Wiley & Sons, Inc.
Bibliometrics:
Citation Count: 1

Fuzzy quantification supplies powerful tools for handling linguistic expressions. Nevertheless, its advantages are usually shown at the theoretical level without a proper empirical validation. In this work, we review the application of fuzzy quantification in two application domains. We provide empirical evidence on the adequacy of fuzzy quantification to support ...

19 published by ACM
October 2008 CIKM '08: Proceedings of the 17th ACM conference on Information and knowledge management
Publisher: ACM
Bibliometrics:
Citation Count: 7
Downloads (6 Weeks): 0,   Downloads (12 Months): 4,   Downloads (Overall): 281

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The scope hypothesis in Information Retrieval (IR) states that a relationship exists between document length and relevance, such that the likelihood of relevance increases with document length. A number of empirical studies have provided statistical evidence supporting the scope hypothesis. However, these studies make the implicit assumption that modern test ...
Keywords: document length, relevance, pooling, evaluation, information retrieval

20 published by ACM
October 2008 IIiX '08: Proceedings of the second international symposium on Information interaction in context
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 2,   Downloads (12 Months): 7,   Downloads (Overall): 120

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Current Information Retrieval systems are often based on topicality. They estimate relevance by comparing the similarity between the user query and each document. These systems do not take into account important contextual information. More specifically, they do not often apply mechanisms to filter out redundant information. We interpret context here ...



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