Question classification using support vector machines

Zhang, Dell; Lee, Wee Sun

doi:10.1145/860435.860443

Cited by 373 publications

(118 citation statements)

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“…SVM has shown good performance for many natural language related applications, such as text classification (Joachims 2002), and has been used in multiple studies relating to question classification (Blooma et al 2008;Tamura, Takamura and Okumura 2005;Solorio et al 2004;Zhang and Lee 2003). Table 4 summarizes the performance of all the classifiers evaluated in our experiment.…”

Section: F) Classifier Training and Testingmentioning

confidence: 99%

Community Engagement and Quality Knowledge with Stackoverflow’s Reputation System: Applications to Bullipedia

Jiménez-Mavillard

Suárez

2018

Digital Studies/Le Champ Numérique

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Section: F) Classifier Training and Testingmentioning

confidence: 99%

Community Engagement and Quality Knowledge with Stackoverflow’s Reputation System: Applications to Bullipedia

Jiménez-Mavillard

Suárez

2018

Digital Studies/Le Champ Numérique

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“…NLP has investigated methods to categorize questions more accurately and appropriately (work such as Zhang and Lee (2003) discusses these concepts) in order to aid question classification. Additionally, numerous works surrounding the use and motivations of Q&A (e.g., Jeon et al (2010); Dearman and Truong (2010)) are still popular research areas.…”

Section: Related Workmentioning

confidence: 99%

A deniable and efficient question and answer service over ad hoc social networks

2012

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When people are connected together over ad hoc social networks, it is possible to ask questions and retrieve answers using the wisdom of the crowd. However, locating a suitable candidate for answering a specific unique question within larger ad hoc groups is non-trivial, especially if we wish to respect the privacy of users by providing deniability. All members of the network wish to source the best possible answers from the network, while at the same time controlling the levels of attention required to generate them by the collective group of individuals and/or the time taken to read all the answers. Conventional expert retrieval approaches rank users for a given query in a centralised indexing process, associating users with material they have previously published. Such an approach is antithetical to privacy, so we have looked to distribute the routing of questions and answers, converting the indexing process into one of building a forwarding table. Starting from the simple operation of flooding the question to everyone, we compare a number of different routing options, where decisions must be made based on past performance and exploitation of the knowledge of our immediate neighbours. We focus on fully decentralised protocols using ant-inspired tactics to route questions towards members of the network who may be able to answer them well. Simultaneously, privacy concerns are acknowledged by allowing both question asking and answering to be plausibly deniable. We have found that via our routing method, it is possible to improve answer quality and also reduce the total amount of user attention required to generate those answers.

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“…Zhang and Lee (2003) employed tree kernel with a SVM classifier for question classification and reported 80.2% accuracy without the use of syntactic or semantic features. Li and Roth (2002) reported a hierarchical approach for question classification based on the SNoW learning architecture.…”

Section: Related Workmentioning

confidence: 99%