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Measuring similarity in co-occurrence data using ego-networks

• Authors : Wang, Xiaomeng; Ran, Yijun; Jia, Tao

Subjects: Computer Science - Information Retrieval

• Source: Chaos: An Interdisciplinary Journal of Nonlinear Science 30 (2020) 013101

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Multi-view Information-theoretic Co-clustering for Co-occurrence Data

• Authors : Xu, Peng; Deng, Zhaohong; Choi, Kup-Sze

Subjects: Computer Science - Machine Learning; Statistics - Machine Learning

• Source: AAAI 2019

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You shall know a species by the company it keeps: Leveraging co‐occurrence data to improve ecological prediction

• Authors : Siefert, Andrew; Laughlin, Daniel C.; Sabatini, Francesco Maria ...

• Source: Journal of Vegetation Science ; volume 35, issue 6 ; ISSN 1100-9233 1654-1103

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Author Correction: Power laws in species’ biotic interaction networks can be inferred from co-occurrence data

• Authors : Galiana, Nuria; Arnoldi, Jean-François; Mestre, Frederico

• Source: Nature Ecology & Evolution ; volume 8, issue 8, page 1557-1557 ; ISSN 2397-334X

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Power-laws in species' biotic interaction networks can be inferred from co-occurrence data

• Authors : Galiana, Nuria

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Word Clustering and Disambiguation Based on Co-occurrence Data

• Authors : Li, Hang; Abe, Naoki

Subjects: Computer Science - Computation and Language

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A Monte Carlo permutation test for co-occurrence data

• Authors : Kovács, Balázs

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Multi-View Information-Theoretic Co-Clustering for Co-Occurrence Data

• Authors : Cao, L; Xu, P; Deng, Z

Subjects: Conference Proceeding

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Discursive quads: new kinds of lexical co‐occurrence data with linguistic concept modelling

• Authors : Mehl, S.

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Discursive Quads: New Kinds of Lexical Co‐occurrence Data With Linguistic Concept Modelling

• Authors : Mehl, Seth; Arts and Humanities Research Council

• Source: Transactions of the Philological Society ; volume 120, issue 3, page 474-488 ; ISSN 0079-1636 1467-968X

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