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80
Sentiment classification of movie reviews using contextual valence shifters.
- Computational Intelligence,
, 2006
"... We present two methods for determining the sentiment expressed by a movie review. The semantic orientation of a review can be positive, negative, or neutral. We examine the effect of valence shifters on classifying the reviews. We examine three types of valence shifters: negations, intensifiers, an ..."
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Cited by 114 (1 self)
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We present two methods for determining the sentiment expressed by a movie review. The semantic orientation of a review can be positive, negative, or neutral. We examine the effect of valence shifters on classifying the reviews. We examine three types of valence shifters: negations, intensifiers, and diminishers. Negations are used to reverse the semantic polarity of a particular term, while intensifiers and diminishers are used to increase and decrease, respectively, the degree to which a term is positive or negative. The first method classifies reviews based on the number of positive and negative terms they contain. We use the General Inquirer to identify positive and negative terms, as well as negation terms, intensifiers, and diminishers. We also use positive and negative terms from other sources, including a dictionary of synonym differences and a very large Web corpus. To compute corpus-based semantic orientation values of terms, we use their association scores with a small group of positive and negative terms. We show that extending the term-counting method with contextual valence shifters improves the accuracy of the classification. The second method uses a Machine Learning algorithm, Support Vector Machines. We start with unigram features and then add bigrams that consist of a valence shifter and another word. The accuracy of classification is very high, and the valence shifter bigrams slightly improve it. The features that contribute to the high accuracy are the words in the lists of positive and negative terms. Previous work focused on either the term-counting method or the Machine Learning method. We show that combining the two methods achieves better results than either method alone.
Contested Collective Intelligence: Rationale, Technologies, and a Human-Machine Annotation Study
, 2012
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Carusi A: Hypotheses, Evidence and Relationships: The HypER Approach for Representing Scientific Knowledge Claims
, 2009
"... Abstract. Biological knowledge is increasingly represented as a collection of (entity-relationship-entity) triplets. These are queried, mined, appended to papers, and published. However, this representation ignores the argumentation contained within a paper and the relationships between hypotheses, ..."
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Cited by 11 (3 self)
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Abstract. Biological knowledge is increasingly represented as a collection of (entity-relationship-entity) triplets. These are queried, mined, appended to papers, and published. However, this representation ignores the argumentation contained within a paper and the relationships between hypotheses, claims and evidence put forth in the article. In this paper, we propose an alternate view of the research article as a network of ‘hypotheses and evidence’. Our knowledge representation focuses on scientific discourse as a rhetorical activity, which leads to a different direction in the development of tools and processes for modeling this discourse. We propose to extract knowledge from the article to allow the construction of a system where a specific scientific claim is connected, through trails of meaningful relationships, to experimental evidence. We discuss some current efforts and future plans in this area.
Shallow Parsing and Disambiguation Engine
- Proceedings of the 3rd Language & Technology Conference
, 2007
"... This article presents a formalism and a beta version of a new tool for simultaneous morphosyntactic disambiguation and shallow parsing. Unlike in the case of other shallow parsing formalisms, the rules of the grammar allow for explicit morphosyntactic disambiguation statements, independently of stru ..."
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Cited by 10 (2 self)
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This article presents a formalism and a beta version of a new tool for simultaneous morphosyntactic disambiguation and shallow parsing. Unlike in the case of other shallow parsing formalisms, the rules of the grammar allow for explicit morphosyntactic disambiguation statements, independently of structure-building statements, which facilitates the task of the shallow parsing of morphosyntactically ambiguous or erroneously disambiguated input. óń 1.
Forging Agreement: Morphological Disambiguation of Noun Phrases
- In Erhard Hinrichs and Kiril Simov, editors, Proceedings of the First Workshop on Treebanks and Linguistic Theory
"... The paper argues that morphological disambiguation is a crucial step for assignment of dependency structures. Quantitative evaluation on a German corpus shows that morphological disambiguation of NPs together with syntactic heuristics yields unique morphological analyses for the assignment of dep ..."
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Cited by 10 (2 self)
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The paper argues that morphological disambiguation is a crucial step for assignment of dependency structures. Quantitative evaluation on a German corpus shows that morphological disambiguation of NPs together with syntactic heuristics yields unique morphological analyses for the assignment of dependency relations to German NPs in 77.08% of all cases.
Adaptation of Statistical Machine Translation Model for Cross-Lingual Information Retrieval in a Service Context
"... This work proposes to adapt an existing general SMT model for the task of translating queries that are subsequently going to be used to retrieve information from a target language collection. In the scenario that we focus on access to the document collection itself is not available and changes to th ..."
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Cited by 9 (0 self)
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This work proposes to adapt an existing general SMT model for the task of translating queries that are subsequently going to be used to retrieve information from a target language collection. In the scenario that we focus on access to the document collection itself is not available and changes to the IR model are not possible. We propose two ways to achieve the adaptation effect and both of them are aimed at tuning parameter weights on a set of parallel queries. The first approach is via a standard tuning procedure optimizing for BLEU score and the second one is via a reranking approach optimizing for MAP score. We also extend the second approach by using syntax-based features. Our experiments show improvements of 1-2.5 in terms of MAP score over the retrieval with the non-adapted translation. We show that these improvements are due both to the integration of the adaptation and syntax-features for the query translation task. 1
Intertwining Deep Syntactic Processing and Named Entity Detection
- Advances in Natural Language Processing
, 2004
"... Abstract. In this paper, we present a robust incremental architecture for natural language processing centered around syntactic analysis but allowing at the same time the description of specialized modules, like named entity recognition. We show that the flexibility of our approach allows us to int ..."
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Cited by 8 (0 self)
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Abstract. In this paper, we present a robust incremental architecture for natural language processing centered around syntactic analysis but allowing at the same time the description of specialized modules, like named entity recognition. We show that the flexibility of our approach allows us to intertwine general and specific processing, which has a mutual improvement effect on their respective results: for example, syntactic analysis clearly benefits from named entity recognition as a pre-processing step, but named entity recognition can also take advantage of deep syntactic information.
XRCE-T: XIP temporal module for TempEval campaign
"... We present the system we used for the TempEval competition. This system relies on a deep syntactic analyzer that has been extended for the treatment of temporal expressions, thus making temporal processing a complement to a better general purpose text understanding system. 1 General presentation and ..."
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Cited by 7 (0 self)
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We present the system we used for the TempEval competition. This system relies on a deep syntactic analyzer that has been extended for the treatment of temporal expressions, thus making temporal processing a complement to a better general purpose text understanding system. 1 General presentation and system overview Although interest in temporal and aspectual phenomena is not new in NLP and AI, temporal processing of real texts is a topic that has been of growing interest in the last years (Mani et al. 2005). The work we have done concerning temporal processing of texts is part of a more general process
A Finite-State Approach to Shallow Parsing and Grammatical Functions Annotation of German
- Ph.D. thesis, Seminar für Sprachwissenschaft, Universität Tübingen. Version of 16th
, 2005
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2008b. PASSAGE: from french parser evaluation to large sized treebank
- In Proceedings of LREC 2008
"... In this paper we present the PASSAGE project which aims at building automatically a French Treebank of large size by combining the output of several parsers, using the EASY annotation scheme. We present also the results of the of the first evaluation campaign of the project and the preliminary resul ..."
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Cited by 7 (3 self)
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In this paper we present the PASSAGE project which aims at building automatically a French Treebank of large size by combining the output of several parsers, using the EASY annotation scheme. We present also the results of the of the first evaluation campaign of the project and the preliminary results we have obtained with our ROVER procedure for combining parsers automatically. 1.
