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CLGVSM: Adapting Generalized Vector Space Model to Cross-lingual Document Clustering
2011
International Joint Conference on Natural Language Processing
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Experimental results on benchmarking data set show that (1) the proposed CLGVSM is very effective for cross-document clustering, outperforming the two strong baselines vector space model (VSM) and latent ...
semantic analysis (LSA) significantly; and (2) the new feature selection method can further improve CLGVSM. ...
Acknowledgment This work is partially supported by NSFC (60703051) and MOST (2009DFA12970). We thank the reviewers for the valuable comments. ...
dblp:conf/ijcnlp/TangXZLZ11
fatcat:gxmp2fy4lje6xft3kpzzlk2roi
Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction
[article]
2019
arXiv
pre-print
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We present a detailed theoretical and computational analysis of the Watset meta-algorithm for fuzzy graph clustering, which has been found to be widely applicable in a variety of domains. ...
Then, it uses hard clustering to discover clusters in this "disambiguated" intermediate graph. ...
Foundation for Basic Research (RFBR) under the project no. 16-37-00354 мол_а. ...
arXiv:1808.06696v3
fatcat:jdd5cnkhffhaxlti72oskgleye
Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction
2019
Computational Linguistics
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We present a detailed theoretical and computational analysis of the Watset meta-algorithm for fuzzy graph clustering, which has been found to be widely applicable in a variety of domains. ...
Then, it uses hard clustering to discover clusters in this "disambiguated" intermediate graph. ...
We thank Bonaventura Coppolla for discussions and preliminary work on graph-based frame induction and Andrei Kutuzov, who conducted experiments with the HOSG-based baseline related to the frame induction ...
doi:10.1162/coli_a_00354
fatcat:b5dr23gh6var3fnzjdgztzdjni
Morphosyntactic Linguistic Wavelets for Knowledge Management
[chapter]
2012
Intelligent Systems
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Gelernter's perspective on reasoning Section 3.2.3. defines that the clustering algorithms must be used first hard clusterings and afterwards fuzzy. It is not a trivial restriction. ...
That description is analogous to the filtering restriction: define sharp clustering first and leave fuzzy clustering approaches for the final steps. ...
and human support in the healthcare environment have also been made easier. ...
doi:10.5772/35438
fatcat:u446haayojbutoy6cvz6quitdu
Tracking linguistic primitives
[chapter]
2017
Iconicity in Language and Literature
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Significant semantic groupings and relations based solely on phonological contrasts were found for most investigated concepts, including the semantic domains; Small, Intense Vision-Touch, Large, Organic ...
The most notable relations found were; MOTHER/I vs. ...
Several binary oppositional relations were found between the Small and Intense Vision-Touch, and Large-Organic clusters (e.g. SOFT-HARD. ...
doi:10.1075/ill.15.03joh
fatcat:u6dlhusmwvf6jpfjlgifqntye4
Mental representation and cognitive consequences of Chinese individual classifiers
2009
Language and Cognitive Processes
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(See the Chinese classifier dictionaries for additional examples.) ...
speakers, and they also produced the greatest amount of clustering for both Chinese and English speakers. ...
doi:10.1080/01690960802018323
fatcat:x34dtjiw7bfyrl3lezn4fn42za
Multilingual Metaphor Processing: Experiments with Semi-Supervised and Unsupervised Learning
2017
Computational Linguistics
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Our aim is to identify the optimal type of supervision for a learning algorithm that discovers patterns of metaphorical association from text. ...
, unconstrained and constrained clustering settings. ...
Acknowledgments We would like to thank our anonymous reviewers for their most insightful comments. Ekaterina Shutova's research is supported by the Leverhulme Trust Early Career Fellowship. ...
doi:10.1162/coli_a_00275
fatcat:ojrv5y4e4zaifafj6femg7n354
Introduction to information retrieval
2009
ChoiceReviews
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Tomasic and Garcia-Molina (1993) and Jeong and Omiecinski (1995) are key early papers evaluating term partitioning versus document partitioning for distributed indexes. ...
The scheme discussed in this chapter, currently believed to be the best published scheme (achieving as few as 3 bits per link for encoding), is described in a series of papers by Boldi and Vigna (2004b ...
A document about Chinese cars may get soft assignments of 0.5 to each of the two clusters China and automobiles, reflecting the fact that both topics are pertinent. ...
doi:10.5860/choice.46-2715
fatcat:ruwoe46pgzcupjygnwbnit4z3u
Lexikos 30
2020
Lexikos
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Bibliography
Dictionaries
Acknowledgements This research is supported in part by (a) the South African Centre for Digital Language Resources (SADiLaR) and (b) the National Research Foundation of South ...
Acknowledgements This is a substantially expanded, reorganized and rewritten text of the talk entitled "Teaching Lexicography to EFL
Acknowledgements This research is supported by the South African ...
In a particular sentence, the logical-conceptual relations are transformed into syntactic relations. ...
doi:10.5788/30-1-1610
fatcat:6eksuj2d6fef7ijdrvj64vb5zq
Has Computational Linguistics Become More Applied?
[chapter]
2009
Lecture Notes in Computer Science
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We approach the problem of related term identification by constructing low-dimensional embeddings where related terms are clustered together, and such clusters are spatially arranged according to the semantic ...
In this work, we demonstrate the proposed methodology for a specific part-of-speech (verbs) of the Spanish language, by using dictionary-based definitions. ...
Related Work
Semi-supervised Clustering The semi-supervised clustering methods can be classified into constraint-based and distance-based. ...
doi:10.1007/978-3-642-00382-0_1
fatcat:oddvfzds4nfwjam2ccqeaxe2y4
DWIE: An entity-centric dataset for multi-task document-level information extraction
2021
Information Processing & Management
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DWIE is conceived as an entity-centric dataset that describes interactions and properties of conceptual entities on the level of the complete document. ...
Recognition (NER), (ii) Coreference Resolution, (iii) Relation Extraction (RE), and (iv) Entity Linking. ...
Acknowledgements Part of the research leading to these results has received funding from (i) the European Union's Horizon 2020 research and innovation programme under grant agreement no. 761488 for the ...
doi:10.1016/j.ipm.2021.102563
fatcat:s2imreyj7rep7i56fv7cuy2iia
DWIE: an entity-centric dataset for multi-task document-level information extraction
[article]
2021
arXiv
pre-print
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DWIE is conceived as an entity-centric dataset that describes interactions and properties of conceptual entities on the level of the complete document. ...
Recognition (NER), (ii) Coreference Resolution, (iii) Relation Extraction (RE), and (iv) Entity Linking. ...
Acknowledgements Part of the research leading to these results has received funding from (i) the European Union's Horizon 2020 research and innovation programme under grant agreement no. 761488 for the ...
arXiv:2009.12626v2
fatcat:2ht56fk3l5bipgev2uttsnagvu
Strudel: A Corpus-Based Semantic Model Based on Properties and Types
2010
Cognitive Science
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(clustering into superordinates), suggesting the empirical validity of the property-based approach. naturally occurring data, mostly in the form of linguistic corpora, that is, large and typically mixed ...
when acquiring language and conceptual knowledge. ...
Acknowledgments We thank Raffaella Bernardi, Katrin Erk, Alessandro Lenci, and the Cognitive Science editor and reviewers for very useful feedback, as well as the developers of the tools and resources ...
doi:10.1111/j.1551-6709.2009.01068.x
pmid:21564211
fatcat:mrzvpwblmrfu3gncmvce7gok54
Message from the general chair
2015
2015 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)
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To maximize the utility of the injected knowledge, we deploy a learning-based multi-sieve approach and develop novel entity-based features. ...
We propose a joint learning model which combines pairwise classification and mention clustering with Markov logic. ...
Given the exponential size of the mapping space, we propose a novel method for optimizing over soft mappings, and use entropy regularization to drive those towards hard mappings. ...
doi:10.1109/ispass.2015.7095776
dblp:conf/ispass/Lee15
fatcat:ehbed6nl6barfgs6pzwcvwxria
Sentiment Analysis and Opinion Mining
[chapter]
2017
Encyclopedia of Machine Learning and Data Mining
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The constraints can also be relaxed, i.e., they are treated as soft (rather than hard) constraints and may not be satisfied. ...
In other words, it is hard to use the dictionary-based approach to find domain or context dependent orientations of sentiment words. ...
doi:10.1007/978-1-4899-7687-1_907
fatcat:iy5ty44cyzbrtodxfo7osy3iu4
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