[Tzoukermann, E. Klavans, J. Jaquemin, C. Effective Use of Natural Language Processing Techniques for Automatic Conflation of Multi-Word Terms: The Role of Derivational Morphology, Part of Speech Tagging, and Shallow Parsing. SIGIR '97. ACM 1997. P. 148 - 155 Home/Search Document Details and Download
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On-Line New Event Detection, Clustering, And Tracking - Papka (1999) (Correct)
....There are several methods for extracting phrases. N gram models based on mutual information metrics are used to find sets of adjacent words that are likely to cooccur within sentences [9] Part of speech tagging using pre specified syntactic templates or more complex natural language parsing [29, 88] gives rise to related multiple words comprising noun, verb, and prepositional phrases. Riloff and Lehnert [66] use information extraction techniques that build multiword features as an integral part of their message understanding system. In what follows we attempt to embed a statistical natural ....
E. Tzoukermann, J.L. Klavans, and C. Jacquemin, "Effective Use of Natural Language Processing Techniques for Automatic Conflation of Multi-Word Terms: The Role of Derivational Morphology, Part of Speech Tagging, and Shallow Parsing," Proceedings of ACM SIGIR, 148-155, 1997.
Document Classification using Multiword Features - Papka (1998) (2 citations) (Correct)
....reported methods for extracting multiword features. N gram models based on mutual information metrics are used to find sets of adjacent words that are likely to cooccur within sentences [2] Part of speech tagging using prespecified syntactic templates or more complex natural language parsing [9, 21] give rise to related multiple words comprising noun, verb, and prepositional phrases. In general, many of the previous techniques for extracting multiword features are based on finding phrases and multiple words that occur near each other within text; however, our approach suggests that modelling ....
E. Tzoukermann, J.L. Klavans, and C. Jacquemin, "Effective Use of Natural Language Processing Techniques for Automatic Conflation of Multi-Word Terms: The Role of Derivational Morphology, Part of Speech Tagging, and Shallow Parsing," Proceedings of SIGIR, 148-155, 1997.
Conflation-based Comparison of Stemming Algorithms - Fuller, Zobel (1998) (Correct)
....of affixes. Terms match if they have a common root. For example, trains might be stemmed to train , which would match train , training , and of course trains . Each word thus has a set of conflations , that is, words that have the same root. Several stemming algorithms have been proposed [8, 9, 10, 11, 13, 17, 18], based on different principles; each produces rather different sets of conflations. Stemming has usually been measured by its impact on querying: since stemming changes the documents that are retrieved in response to a query, it has the potential to change the quality of the set of answers. ....
Evelyne Tzoukermann, Judith L. Klavans and Christian Jacquemin. Effective use of natural language processing techniques for automatic conflation of multi-word terms: the role of derivational morphology, part of speech tagging, and shallow parsing. In Belkin et al. [1], pages 148--155.
Improving Information Retrieval Systems using Part of Speech.. - Chowdhury, McCabe (Correct)
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[Tzoukermann, E. Klavans, J. Jaquemin, C. Effective Use of Natural Language Processing Techniques for Automatic Conflation of Multi-Word Terms: The Role of Derivational Morphology, Part of Speech Tagging, and Shallow Parsing. SIGIR '97. ACM 1997. P. 148 - 155
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