Predicting future scientific discoveries based on a networked analysis of the past literature

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn 2015-August, Issue , 2015, Pages 2019-2028

  Nagarajan, Meena ^a   Wilkins, Angela D ^c   Bachman, Benjamin J ^c   Novikov, Ilya B ^c   Bao, Shenghua ^a   Haas, Peter J ^a   Terrón Díaz, María E ^c   Bhatia, Sumit ^a   Adikesavan, Anbu K ^c   Labrie, Jacques J ^a   Regenbogen, Sam ^c   Buchovecky, Christie M ^c   Pickering, Curtis R ^b   Kato, Linda ^a   Lisewski, Andreas M ^c   Lelescu, Ana ^a   Zhang, Houyin ^c   Boyer, Stephen ^a   Weber, Griff ^a   Chen, Ying ^a   Donehower, Lawrence ^c   Spangler, Scott ^a   Lichtarge, Olivier ^c   more..

^a IBM ALMADEN RESEARCH CENTER   (United States)

^b UNIVERSITY OF TEXAS MD ANDERSON CANCER CENTER   (United States)

^c BAYLOR COLLEGE OF MEDICINE   (United States)

Author keywords

Hypothesis generation; Scientific discovery; Text mining

Indexed keywords

FACTORIZATION; FORECASTING; NATURAL LANGUAGE PROCESSING SYSTEMS; PROTEINS;

HYPOTHESIS GENERATION; KNOWLEDGE EXTRACTION; KNOWLEDGE INTEGRATION; MATRIX FACTORIZATIONS; PROTEIN-PROTEIN INTERACTIONS; SCIENTIFIC DISCOVERY; SCIENTIFIC LITERATURE; TEXT MINING;

DATA MINING;

EID: 84954121316     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2783258.2788609     Document Type: Conference Paper

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