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Displaying 1-16 out of 16 total
Technologies That Make You Smile: Adding Humor to Text-Based Applications
Found in: IEEE Intelligent Systems
By Rada Mihalcea, Carlo Strapparava
Issue Date:September 2006
pp. 33-39
Humor is an aspect of human behavior that many people consider essential for interpersonal communication. Despite this, research in human-computer interaction has almost completely neglected aspects concerned with the automatic recognition, generation, or ...
Utilizing Semantic Composition in Distributional Semantic Models for Word Sense Discrimination and Word Sense Disambiguation
Found in: 2012 IEEE Sixth International Conference on Semantic Computing (ICSC)
By Cem Akkaya,Janyce Wiebe,Rada Mihalcea
Issue Date:September 2012
pp. 45-51
Semantic composition in distributional semantic models (DSMs) offers a powerful tool to represent word meaning in context. In this paper, we investigate methods to utilize compositional DSMs to improve word sense discrimination and word sense disambiguatio...
Linking Documents to Encyclopedic Knowledge
Found in: IEEE Intelligent Systems
By Andras Csomai, Rada Mihalcea
Issue Date:September 2008
pp. 34-41
Wikipedia can support the development of automatic methods for keyword extraction and word-sense disambiguation. The Wikify system combines these two methods to automatically enrich a text with links to Wikipedia content. The system identifies the importan...
Unsupervised Graph-basedWord Sense Disambiguation Using Measures of Word Semantic Similarity
Found in: International Conference on Semantic Computing
By Ravi Sinha, Rada Mihalcea
Issue Date:September 2007
pp. 363-369
This paper describes an unsupervised graph-based method for word sense disambiguation, and presents comparative evaluations using several measures of word semantic similarity and several algorithms for graph centrality. The results indicate that the right ...
Random-Walk Term Weighting for Improved Text Classification
Found in: International Conference on Semantic Computing
By Samer Hassan, Rada Mihalcea, Carmen Banea
Issue Date:September 2007
pp. 242-249
This paper describes a new approach for estimating term weights in a document, and shows how the new weighting scheme can be used to improve the accuracy of a text classifier. The method uses term co-occurrence as a measure of dependency between word featu...
Using WordNet and Lexical Operators to Improve Internet Searches
Found in: IEEE Internet Computing
By Dan I. Moldovan, Rada Mihalcea
Issue Date:January 2000
pp. 34-43
<p>A natural language interface system for an Internet search engine shows substantial increases in the precision of query results and the percentage of queries answered correctly. The system expands queries based on a word-sense-disambiguation metho...
Multimodal Sentiment Analysis of Spanish Online Videos
Found in: IEEE Intelligent Systems
By Veronica Perez Rosas,Rada Mihalcea,Louis-Philippe Morency
Issue Date:May 2013
pp. 38-45
Using multimodal sentiment analysis, the presented method integrates linguistic, audio, and visual features to identify sentiment in online videos. In particular, experiments focus on a new dataset consisting of Spanish videos collected from YouTube that a...
Porting Multilingual Subjectivity Resources across Languages
Found in: IEEE Transactions on Affective Computing
By Carmen Banea,Rada Mihalcea,Janyce Wiebe
Issue Date:April 2013
pp. 211-225
Subjectivity analysis focuses on the automatic extraction of private states in natural language. In this paper, we explore methods for generating subjectivity analysis resources in a new language by leveraging on the tools and resources available in Englis...
Automatic detection of deceit in verbal communication
Found in: Proceedings of the 15th ACM on International conference on multimodal interaction (ICMI '13)
By Rada Mihalcea, Mihai Burzo, Verónica Pérez-Rosas
Issue Date:December 2013
pp. 131-134
This paper presents experiments in building a classifier for the automatic detection of deceit. Using a dataset of deceptive videos, we run several comparative evaluations focusing on the verbal component of these videos, with the goal of understanding the...
Thermal imaging for affect detection
Found in: Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA '13)
By Alexis Narvaez, Mihai Burzo, Rada Mihalcea, Verónica Pérez-Rosas
Issue Date:May 2013
pp. 1-4
In this paper, we explore a thermal imaging approach to sensing affective state. Using features extracted from a thermal map of the face, obtained from a dataset consisting of 70 recordings of positive, negative, or neutral states, we show that we can effe...
Towards multimodal deception detection -- step 1: building a collection of deceptive videos
Found in: Proceedings of the 14th ACM international conference on Multimodal interaction (ICMI '12)
By Mihai Burzo, Rada Mihalcea
Issue Date:October 2012
pp. 189-192
In this paper, we introduce a novel crowdsourced dataset of deceptive videos. We describe the collection process and the characteristics of the dataset, and we validate it through initial experiments in the recognition of deceptive language. The collection...
Towards sensing the influence of visual narratives on human affect
Found in: Proceedings of the 14th ACM international conference on Multimodal interaction (ICMI '12)
By Alexis Narvaez, Daniel McDuff, Louis-Philippe Morency, Mihai Burzo, Rada Mihalcea, Veronica Perez-Rosas
Issue Date:October 2012
pp. 153-160
In this paper, we explore a multimodal approach to sensing affective state during exposure to visual narratives. Using four different modalities, consisting of visual facial behaviors, thermal imaging, heart rate measurements, and verbal descriptions, we s...
Towards multimodal sentiment analysis: harvesting opinions from the web
Found in: Proceedings of the 13th international conference on multimodal interfaces (ICMI '11)
By Louis-Philippe Morency, Payal Doshi, Rada Mihalcea
Issue Date:November 2011
pp. 169-176
With more than 10,000 new videos posted online every day on social websites such as YouTube and Facebook, the internet is becoming an almost infinite source of information. One crucial challenge for the coming decade is to be able to harvest relevant infor...
Learning to identify educational materials
Found in: ACM Transactions on Speech and Language Processing (TSLP)
By Rada Mihalcea, Samer Hassan
Issue Date:November 2011
pp. 1-18
In this article, we explore the task of automatically identifying educational materials by classifying documents with respect to their educational value. Through experiments carried out on a dataset of manually annotated documents, we show that the general...
Learning to identify emotions in text
Found in: Proceedings of the 2008 ACM symposium on Applied computing (SAC '08)
By Carlo Strapparava, Rada Mihalcea
Issue Date:March 2008
pp. 28-34
This paper describes experiments concerned with the automatic analysis of emotions in text. We describe the construction of a large data set annotated for six basic emotions: ANGER, DISGUST, FEAR, JOY, SADNESS and SURPRISE, and we propose and evaluate seve...
Semantic document engineering with WordNet and PageRank
Found in: Proceedings of the 2005 ACM symposium on Applied computing (SAC '05)
By Elizabeth Figa, Paul Tarau, Rada Mihalcea
Issue Date:March 2005
pp. 782-786
This paper describes Natural Language Processing techniques for document engineering in combination with graph algorithms and statistical methods. Google's PageRank and similar fast-converging recursive graph algorithms have provided practical means to sta...