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Making Computers Laugh: Investigations in Automatic Humor Recognition
Date: October 2005
Creator: Mihalcea, Rada, 1974- & Strapparava, Carlo, 1962-
Description: This paper discusses investigations in automatic humor recognition. Abstract: Humor is one of the most interesting and puzzling aspects of human behavior. Despite the attention it has received in fields such as philosophy, linguistics, and psychology, there have been only few attempts to create computational models for humor recognition or generation. In this paper, we bring empirical evidence that computational approaches can be successfully applied to the task of humor recognition. Through experiments performed on very large data sets, we show that automatic classification techniques can be effectively used to distinguish between humorous and non-humorous texts, with significant improvements observed over apriori known baselines.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc30968/
A Language Independent Algorithm for Single and Multiple Document Summarization
Date: October 2005
Creator: Mihalcea, Rada, 1974- & Tarau, Paul
Description: This paper discusses a language independent algorithm for single and multiple document summarization. Abstract: This paper describes a method for language independent extractive summarization that relies on iterative graph-based ranking algorithms. Through evaluations performed on a single document summarization task for English and Portuguese, we show that the method performs equally well regardless of the language. Moreover, we show how a meta-summarizer relying on a layered application of techniques for single-document summarization can be turned into an effective method for multi-document summarization.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc30965/
Learning Multilingual Subjective Language via Cross-Lingual Projections
Date: June 2007
Creator: Mihalcea, Rada, 1974-; Banea, Carmen & Wiebe, Janyce M.
Description: This paper discusses learning multilingual subjective language via cross-lingual projections. Abstract: This paper explores methods for generating subjectivity analysis resources in a new language by leveraging on the tools and resources available in English. Given a bridge between English and the selected target language (e.g., a bilingual dictionary or a parallel corpus), the methods can be used to rapidly create tools for subjectivity analysis in the new language.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc30991/
Corpus-based and Knowledge-based Measures of Text Semantic Similarity
Date: July 2006
Creator: Mihalcea, Rada, 1974-; Corley, Courtney & Strapparava, Carlo, 1962-
Description: Abstract: This paper presents a method for measuring the semantic similarity of texts, using corpus-based and knowledge-based measures of similarity. Previous work on this problem has focused mainly on either large documents (e.g. text classification, information retrieval) or individual words (e.g. synonymy tests). Given that a large fraction of the information available today, on the Web and elsewhere, consists of short text snippets (e.g. abstracts of scientific documents, image captions, product descriptions), in this paper the authors focus on measuring the semantic similarity of short texts. Through experiments performed on a paraphrase data set, the authors show that the semantic similarity method out-performs methods based on simple lexical matching, resulting in up to 13% error rate reduction with respect to the traditional vector-based similarity metric.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc30981/
An Evaluation Exercise for Romanian Word Sense Disambiguation
Date: July 2004
Creator: Mihalcea, Rada, 1974-; Nastase, Vivi; Chklovski, Timothy A. (Timothy Anatolievich), 1977; Tatar, Doina; Tufis, Dan & Hristea, Florentina T.
Description: This paper discusses an evaluation exercise for Romanian word sense disambiguation. Abstract: This paper presents the task definition, resources, participating systems, and comparative results for a Romanian Word Sense Disambiguation task, which was organized as part of the SENSEVAL-3 evaluation exercise. Five teams with a total of seven systems were drawn to this task.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc30954/
Computational Models for Incongruity Detection in Humour
Date: March 2010
Creator: Mihalcea, Rada, 1974-; Strapparava, Carlo, 1962- & Pulman, Stephen
Description: This paper discusses computational models for incongruity resolution. Abstract: Incongruity resolution is one of the most widely accepted theories of humor, suggesting that humor is due to the mixing of two disparate interpretation frames in one statement. In this paper, the authors explore several computational models for incongruity resolution. The authors introduce a new data set, consisting of a series of 'set-ups' (preparations for a punch line), each of them followed by four possible coherent continuations out of which only one has a comic effect. Using this data set, the authors redefine the task as the automatic identification of the humorous punch line among all the plausible endings. The authors explore several measures of semantic relatedness, along with a number of joke-specific features, and try to understand their appropriateness as computational models for incongruity detection.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc31024/
The SENSEVAL-3 English Lexical Sample Task
Date: July 2004
Creator: Mihalcea, Rada; Chklovski, Timothy & Kilgarriff, Adam
Description: This paper presents the task definition, resources, participating systems, and comparative results for the English lexical sample task, which was organized as part of the SENSEVAL-3 evaluation exercise. The task drew the participation of 27 teams from around the world, with a total of 47 systems.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc30963/
UNT-Yahoo: SuperSenseLearner: Combining SenseLearner with SuperSense and other Coarse Semantic Features
Date: June 2007
Creator: Mihalcea, Rada; Csomai, Andras & Ciaramita, Massimiliano
Description: In this paper, the authors describe the SuperSenseLearner system that participated in the English all-words disambiguation task. The system relies on automatically-learned semantic models using collocational features coupled with features extracted from the annotations of coarse-grained semantic categories generated by an HMM tagger.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc30998/
NLP (Natural Language Processing) for NLP (Natural Language Programming)
Date: February 2006
Creator: Mihalcea, Rada; Liu, Hugo & Lieberman, Henry
Description: This paper discusses Natural Language Processing (NLP). NLP holds great promise for making computer interfaces that are easier to use for people, since people will (hopefully) be able to talk to the computer in their own language, rather than learn a specialized language of computer commands. For programming, however, the necessity of a formal programming language for communicating with a computer has always been taken for granted. The authors would like to challenge this assumption. The authors believe that modern Natural Language Processing techniques can make possible the use of natural language to (at least partially) express programming ideas, thus drastically increasing the accessibility of programming to non-expert users. To demonstrate the feasibility of Natural Language Programming, this paper tackles what are perceived to be some of the hardest cases: steps and loops. The authors look at a corpus of English descriptions used as programming assignments, and develop some techniques for mapping linguistic constructs onto program structures, which we refer to as programmatic semantics.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc30984/
SemEval-2010 Task 2: Cross-Lingual Lexical Substitution
Date: July 2010
Creator: Mihalcea, Rada; Sinha, Ravi & McCarthy, Diana
Description: In this paper, the authors describe the SemEval-2010 Cross-Lingual Lexical Substitution task, where given an English target word in context, participating systems had to find an alternative substitute word or phrase in Spanish. The task is based on the English Lexical Substitution task run at SemEval-2007. In this article, the authors provide background and motivation for the task, the authors describe the data annotation process and the scoring system, and present the results of the participating systems.
Contributing Partner: UNT College of Engineering
Permallink:digital.library.unt.edu/ark:/67531/metadc31027/