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Modelling Grammar Growth; Universal grammar without innate principles or parameters
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In: http://www.cogsci.uiuc.edu/~green/csout.ps (1998)
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47 |
Modelling Grammar Growth; Universal grammar without innate principles or parameters
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In: http://lees.cogsci.uiuc.edu/~green/csout.ps (1994)
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48 |
Snitch: Augmenting Hypertext Documents With A Semantic Net
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In: http://www.cs.umbc.edu/~nicholas/pubs/snitch/paper.ps (1993)
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Snitch: Augmenting Hypertext Documents With A Semantic Net
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In: http://www.cs.umbc.edu/~mayfield/pubs/ijicis93.ps (1993)
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50 |
Polymorphic Type Inference and Abstract Data Types
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In: DTIC AND NTIS (1992)
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51 |
Um sistema de tipos para uma linguagem de representacao estruturada de conhecimento ; A type sistems for a knowledge structured representation language
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52 |
Um sistema de tipos para uma linguagem de representacao estruturada de conhecimento ; A type sistems for a knowledge structured representation language
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56 |
Capturing the Adjective
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In: Doctoral Dissertations 1896 - February 2014 (1976)
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57 |
Event Types
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In: http://mindmodeling.org/cogsci2010/papers/0464/paper0464.pdf
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58 |
Modelling Grammar Growth; Universal grammar without innate principles or parameters
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In: http://www.ai.mit.edu/people/jimmylin/papers/GreenG97.ps
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59 |
Formalizing UMLS Relations Using Semantic Partitions in the Context of Task-Based Clinical Guidelines Model
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In: http://www.uni-leipzig.de/~akumar/UMLS_partitions.pdf
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60 |
Utilizing Sentence Similarity and Question Type Similarity to Response to Similar Questions in Knowledge-Sharing Community
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In: http://www.pages.drexel.edu/~pa442/pdf/qaweb2008.pdf
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Abstract:
Reusing information redundancy in question-answer pairs is one of the alternative approaches to question answering (QA) system. If the same question has been asked by other users, the QA system responses to such question using the answer associated with the redundant question. Nevertheless, the task of identifying similarity of questions is not trivial. Traditional text similarity measures are neither effective nor efficient in distinguishing the similarity of sentence-level text. Document similarity techniques are not effective since the length of sentence text is rather short and contains very little word overlap. Furthermore, the similarity and relevance of sentences can be characterized into different levels, which is difference than a standard topicality notion used in document retrieval. In this paper, we focus on the problem of identifying questions that express the same information need. The main goal is to match questions with their paraphrases. To achieve this, we propose a hybrid question similarity approach that combines semantic, syntactic, and question type similarity. Semantic and syntactic information is measured by taking into account word similarity, word ordering, and parts of speech information. Information about the types of question is derived from a Support Vector Machine classifier. The experimental results have shown that our approach is highly effective in detecting redundant questions.
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Keyword:
question answering; Question reuse; question similarity; question types. Copyright is held by the author/owner(s; semantic and syntactic techniques
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.218.8165 http://www.pages.drexel.edu/~pa442/pdf/qaweb2008.pdf
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