Head-driven statistical models for natural language parsing are the most representative lexicalized syntactic parsing models, but they only utilize semantic dependency between words, and do not incorporate other seman...
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Head-driven statistical models for natural language parsing are the most representative lexicalized syntactic parsing models, but they only utilize semantic dependency between words, and do not incorporate other semantic information such as semantic collocation and semantic category. Some improvements on this distinctive parser are presented. Firstly, "valency" is an essential semantic feature of words. Once the valency of word is determined, the collocation of the word is clear, and the sentence structure can be directly derived. Thus, a syntactic parsing model combining valence structure with semantic dependency is purposed on the base of head-driven statistical syntactic parsing models. Secondly, semantic role labeling(SRL) is very necessary for deep natural language processing. An integrated parsing approach is proposed to integrate semantic parsing into the syntactic parsing process. Experiments are conducted for the refined statistical parser. The results show that 87.12% precision and 85.04% recall are obtained, and F measure is improved by 5.68% compared with the head-driven parsing model introduced by Collins.
Location-Based services guide a user to find the object which provides services located in a particular position or region (e.g., looking for a coffee shop near a university). Given a query location and multiple keywo...
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The volume of RDF data increases very fast within the last five years, e.g. the Linked Open data cloud grows from 2 billions to 50 billions of RDF triples. With its wonderful scalability, cloud computing platform like...
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With the rapid increase of data volume, more and more applications have to be implemented in a distributed environment. In order to obtain high performance, we need to carefully divide the whole dataset into multiple ...
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We present TYG (Tag-as-You-Go) in this paper, a chrome browser extension for personal knowledge annotation on standard web pages. We investigate an approach to combine a K-Medoid-style clustering algorithm with the us...
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Current studies on association rule mining focus on finding Boolean/quantitative association rules from certain databases or Boolean association rules from probabilistic databases. However, little work on mining assoc...
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In traditional pseudo feedback, the main reason of the topic drift is the low quality of the feedback source. Clustering search results is an effective way to improve the quality of feedback set. For XML data, how to ...
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Modern educational theories, such as collaborative learning, constructivism and inquiry learning, have achieved many successes in real-world applications. Especially, with the development of information technologies, ...
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ISBN:
(纸本)9780889869431
Modern educational theories, such as collaborative learning, constructivism and inquiry learning, have achieved many successes in real-world applications. Especially, with the development of information technologies, there have been several online collaborative learning platforms in practice. Unfortunately, as these platforms are either too complicated or too expensive, none of them are suitable for us in the practice of STEM+. Moreover, most of these platforms are in English, while we are using Chinese as our teaching language. Using an online collaborative learning platform (OCLP) named Zask, this paper reported our practice in online collaborative learning on course Introduction to database System. According to the data collected from the first round of our practice, it shows that users' active participations in Zask could benefit for both teaching and learning, and then provide positive effects in education.
How to determine the truthfulness of a piece of information becomes an increasingly urgent need for users. In this paper, we propose a method called MFSV, to determine the truthfulness of fact statements. We first cal...
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Untruthful information spreads on the web, which may mislead users or have a negative impact on user experience. In this paper, we propose a method called Multi-verifier to determine the truthfulness of a fact stateme...
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