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20,092
Individual Word Probability Models
- Web Journal of Formal, Computational & Cognitive Linguistics (FCCL), Issue 10, Russian Association of Artificial Intelligence
, 2008
"... It is shown that the enormous improvement in the size of disk storage space in recent years can be used to build individual word-domain statistical language models, one for each significant word of a language. Each of these word-domain language models is a precise domain model for the relevant signi ..."
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Cited by 1 (1 self)
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It is shown that the enormous improvement in the size of disk storage space in recent years can be used to build individual word-domain statistical language models, one for each significant word of a language. Each of these word-domain language models is a precise domain model for the relevant
Measuring individual differences in implicit cognition: The implicit association test
- J PERSONALITY SOCIAL PSYCHOL 74:1464–1480
, 1998
"... An implicit association test (IAT) measures differential association of 2 target concepts with an attribute. The 2 concepts appear in a 2-choice task (e.g., flower vs. insect names), and the attribute in a 2nd task (e.g., pleasant vs. unpleasant words for an evaluation attribute). When instructions ..."
Abstract
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Cited by 1008 (63 self)
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An implicit association test (IAT) measures differential association of 2 target concepts with an attribute. The 2 concepts appear in a 2-choice task (e.g., flower vs. insect names), and the attribute in a 2nd task (e.g., pleasant vs. unpleasant words for an evaluation attribute). When instructions
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
- In Proceedings of the 20th International Joint Conference on Artificial Intelligence
, 2007
"... Computing semantic relatedness of natural language texts requires access to vast amounts of common-sense and domain-specific world knowledge. We propose Explicit Semantic Analysis (ESA), a novel method that represents the meaning of texts in a high-dimensional space of concepts derived from Wikipedi ..."
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Cited by 562 (9 self)
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with the previous state of the art, using ESA results in substantial improvements in correlation of computed relatedness scores with human judgments: from r =0.56 to 0.75 for individual words and from r =0.60 to 0.72 for texts. Importantly, due to the use of natural concepts, the ESA model is easy to explain
Learning individual words and learning about words simultaneously
"... Children are guided by constraints and biases in word learning. In the case of the shape bias—the tendency to extend count nouns by similarity in shape—previous findings have revealed that learning plays an important role in its development (e.g., Smith et al., 2002). Some have proposed that childre ..."
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overhypotheses about the role of arbitrary features, not just shape, in determining how words refer to object categories. This work suggests that when learning individual words, children are also learning about words simultaneously. Children’s ability to “learn to learn ” may have implications for the origins
Using Linear Algebra for Intelligent Information Retrieval
- SIAM REVIEW
, 1995
"... Currently, most approaches to retrieving textual materials from scientific databases depend on a lexical match between words in users' requests and those in or assigned to documents in a database. Because of the tremendous diversity in the words people use to describe the same document, lexical ..."
Abstract
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Cited by 676 (18 self)
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Currently, most approaches to retrieving textual materials from scientific databases depend on a lexical match between words in users' requests and those in or assigned to documents in a database. Because of the tremendous diversity in the words people use to describe the same document
Yago: A Core of Semantic Knowledge
- IN PROC. OF WWW ’07
, 2007
"... We present YAGO, a light-weight and extensible ontology with high coverage and quality. YAGO builds on entities and relations and currently contains roughly 900,000 entities and 5,000,000 facts. This includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as hasWonPrize ..."
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Cited by 504 (66 self)
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WonPrize). The facts have been automatically extracted from the unification of Wikipedia and WordNet, using a carefully designed combination of rule-based and heuristic methods described in this paper. The resulting knowledge base is a major step beyond WordNet: in quality by adding knowledge about individuals like
The Generative Lexicon
- Computational Linguistics
, 1991
"... this paper, I will discuss four major topics relating to current research in lexical semantics: methodology, descriptive coverage, adequacy of the representation, and the computational usefulness of representations. In addressing these issues, I will discuss what I think are some of the central prob ..."
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Cited by 1341 (45 self)
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semantic expressions. I develop a theory of Qualia Structure, a representation language for lexical items, which renders much lexical ambiguity in the lexicon unnecessary, while still explaining the systematic polysemy that words carry. Finally, I discuss how individual lexical structures can be integrated
Maximizing the Spread of Influence Through a Social Network
- In KDD
, 2003
"... Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the sudden and widespread adoption of various strategies in game-theoretic settings, and the effects of ..."
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Cited by 990 (7 self)
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of “word of mouth ” in the promotion of new products. Recently, motivated by the design of viral marketing strategies, Domingos and Richardson posed a fundamental algorithmic problem for such social network processes: if we can try to convince a subset of individuals to adopt a new product or innovation
N-gram based Language Identification of Individual Words
"... Abstract—Various factors influence the accuracy with which the language of individual words can be classified using n-grams. We consider a South African text-based language identification (LID) task and experiment with two different types of n-gram classifiers: a Naı̈ve Bayes classifier and a Suppor ..."
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Abstract—Various factors influence the accuracy with which the language of individual words can be classified using n-grams. We consider a South African text-based language identification (LID) task and experiment with two different types of n-gram classifiers: a Naı̈ve Bayes classifier and a
A Post-Processing System To Yield Reduced Word Error Rates: Recognizer Output Voting Error Reduction (ROVER)
, 1997
"... This paper describes a system developed at NIST to produce a composite Automatic Speech Recognition (ASR) system output when the outputs of multiple ASR systems are available, and for which, in many cases, the composite ASR output has lower error rate than any of the individual systems. The system i ..."
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Cited by 422 (2 self)
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This paper describes a system developed at NIST to produce a composite Automatic Speech Recognition (ASR) system output when the outputs of multiple ASR systems are available, and for which, in many cases, the composite ASR output has lower error rate than any of the individual systems. The system
Results 1 - 10
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20,092
