Topic
Semantic similarity
About: Semantic similarity is a research topic. Over the lifetime, 14605 publications have been published within this topic receiving 364659 citations. The topic is also known as: semantic relatedness.
Papers published on a yearly basis
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01 Jan 1973TL;DR: The authors reviewed the structural relationship between syntactic and semantic in children's utterances and found that children start their syntactic careers by learning simple order rules for combining words, which, in their understanding, perform semantic functions such as agent, action, and object acted upon.
Abstract: Publisher Summary
This chapter reviews the structural relationship between syntactic and semantic in children's utterances. According to the view of language acquisition, the linguistic knowledge that lies behind children's initial attempts at word combining may not and need not include information about the basic grammatical relations or the constituent structure they entail. There is, in any event, no compelling evidence as yet that it does. The characteristics of cross-linguistic data suggest the alternative view that children launch their syntactic careers by learning simple order rules for combining words, which, in their understanding, perform semantic functions such as agent, action, and object acted upon, or perhaps other even less abstract semantic functions. Through additional linguistic experience, children may begin to recognize similarities in the way different semantic concepts are formally dealt with and to gradually reorganize their knowledge according to the more abstract grammatical relationships, which are functional in the particular language they are learning.
82 citations
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30 Jul 2007TL;DR: This paper proposes using semantic information as an extension of the dependency structure language model in order to reduce the number of stories retrieved by the system, and get a high precision in topic detection and tracking.
Abstract: In this paper, an idea of adding semantic role to the dependency structure language model is proposed. Firstly, the dependency structure language model for topic detection and tracking is presented. Then we introduce the method to determine the semantic role for the constituents of a sentence. Finally, we add the semantic role to the dependency structure language model Compare the verbs of the sentences in the stories with a list of verbs related with the verb of the topic. Then, annotate the verbs with semantic roles. This can enable us establish a relation between topics and semantic roles. So, only stories whose sentences containing the right semantic roles are selected. We propose using this semantic information as an extension of the dependency structure language model in order to reduce the number of stories retrieved by the system, and get a high precision in topic detection and tracking.
82 citations
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01 Nov 2011TL;DR: This paper proposes a topic model incorporated with the category information into the process of discovering the latent topics in the content of questions and combines the semantic similarity based latent topics with the translation-based language model into a unified framework for question retrieval.
Abstract: Community-based Question Answering (cQA) is a popular online service where users can ask and answer questions on any topics. This paper is concerned with the problem of question retrieval. Question retrieval in cQA aims to find historical questions that are semantically equivalent or relevant to the queried questions. Although the translation-based language model (Xue et al., 2008) has gained the state-of-the-art performance for question retrieval, they ignore the latent topic information in calculating the semantic similarity between questions. In this paper, we propose a topic model incorporated with the category information into the process of discovering the latent topics in the content of questions. Then we combine the semantic similarity based latent topics with the translation-based language model into a unified framework for question retrieval. Experiments are carried out on a real world cQA data set from Yahoo! Answers. The results show that our proposed method can significantly improve the question retrieval performance of translation-based language model.
82 citations
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22 Nov 2009TL;DR: A matching algorithm SMA between cloud computing services of multiple input/output parameters, which considers the semantic similarity of concepts in parameters based on WordNet to show that this approach has better efficiency of service composition than traditional approaches.
Abstract: In this paper, we put forward a matching algorithm SMA between cloud computing services of multiple input/output parameters, which considers the semantic similarity of concepts in parameters based on WordNet. Moreover, a highly efficacious service composition algorithm Fast-EP and the improved FastB+-EP are presented. Then QoS information is utilized to rank the search results. At last, we show through experiment that our approach has better efficiency of service composition than traditional approaches.
82 citations
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TL;DR: TheSemantic Data Warehouse is proposed to be a repository of ontologies and semantically annotated data resources and an ontology-driven framework to design multidimensional analysis models for Semantic Data Warehouses is proposed.
Abstract: The Semantic Web enables organizations to attach semantic annotations taken from domain and application ontologies to the information they generate. The concepts in these ontologies could describe the facts, dimensions and categories implied in the analysis subjects of a data warehouse. In this paper we propose the Semantic Data Warehouse to be a repository of ontologies and semantically annotated data resources. We also propose an ontology-driven framework to design multidimensional analysis models for Semantic Data Warehouses. This framework provides means for building a Multidimensional Integrated Ontology (MIO) including the classes, relationships and instances that represent interesting analysis dimensions, and it can be also used to check the properties required by current multidimensional databases (e.g., dimension orthogonality, category satisfiability, etc.) In this paper we also sketch how the instance data of a MIO can be translated into OLAP cubes for analysis purposes. Finally, some implementation issues of the overall framework are discussed.
82 citations