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1
Informative Causality Extraction from Medical Literature via Dependency-tree based Patterns ...
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2
Navigating the Kaleidoscope of COVID-19 Misinformation Using Deep Learning ...
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3
Redditors in Recovery: Text Mining Reddit to Investigate Transitions into Drug Addiction
In: ArXiv (2018)
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4
Query Segmentation For E-Commerce Sites
Gong, Xiaojing. - 2013
Abstract: Indiana University-Purdue University Indianapolis (IUPUI) ; Query segmentation module is an integral part of Natural Language Processing which analyzes users' query and divides them into separate phrases. Published works on the query segmentation focus on the web search using Google n-gram frequencies corpus or text retrieval from relational databases. However, this module is also useful in the domain of E-Commerce for product search. In this thesis, we will discuss query segmentation in the context of the E-Commerce area. We propose a hybrid unsupervised segmentation methodology which is based on prefix tree, mutual information and relative frequency count to compute the score of query pairs and involve Wikipedia for new words recognition. Furthermore, we use two unique E-Commerce evaluation methods to quantify the accuracy of our query segmentation method.
Keyword: Computational linguistics; E-Commerce; Electronic commerce -- Computer programs; Information storage and retrieval systems; Natural language processing (Computer science); Pattern recognition systems; prefix tree; Query languages (Computer science); Query Segmentation; unsupervised segmentation
URL: https://doi.org/10.7912/C2/2296
https://hdl.handle.net/1805/3364
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5
A-Coord input: augmented pen-based interactions by combining auxiliary input channels
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6
Harmonic modification and data adaptive filtering based approach to robust pitch estimation
In: International journal of speech technology. - Boston, Mass. [u.a.] : Kluwer Acad. Publ. 14 (2011) 4, 339-349
BLLDB
OLC Linguistik
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7
Robust speech dereverberation based on blind adaptive estimation of acoustic channels
In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 19 (2011) 4, 775-787
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OLC Linguistik
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