Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Robert J. Hilderman"'
Publikováno v:
DSAA
We present a novel method for classifying hashtag types. Specifically, we apply word segmentation algorithms and lexical resources in order to classify two types of hashtags: those with sentiment information and those without. However, the complex st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9f49d9f23d207a2901ba5e214cce63be
https://doi.org/10.1109/dsaa.2016.80
https://doi.org/10.1109/dsaa.2016.80
Knowledge Discovery and Measures of Interest is a reference book for knowledge discovery researchers, practitioners, and students. The knowledge discovery researcher will find that the material provides a theoretical foundation for measures of intere
Publikováno v:
Intelligent Data Analysis. 7:347-382
When mining a large database, the number of patterns discovered can easily exceed the capabilities of a human user to identify interesting results. To address this problem, various techniques have been suggested to reduce and/or order the patterns pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ae98dcece21636b73b7eec0dfa482ca
https://doi.org/10.3233/ida-2003-7406
https://doi.org/10.3233/ida-2003-7406
Autor:
Credell Simeon, Robert J. Hilderman
Publikováno v:
WASSA@EMNLP
This paper seeks to identify sentiment and non-sentiment bearing hashtags by com- bining existing lexical resources. By using a lexicon-based approach, we achieve 86.3% and 94.5% precision in identifying sentiment and non-sentiment hashtags, respecti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b7348a81c37ed35675a1eb15fd356256
https://doi.org/10.18653/v1/w15-2924
https://doi.org/10.18653/v1/w15-2924
Autor:
Credell Simeon, Robert J. Hilderman
Publikováno v:
Discovery Science ISBN: 9783319242811
Discovery Science
Discovery Science
Recently, there has been growing research interest in the sentiment analysis of tweets. However, there is still a need to examine the contribution of Twitter-specific features to this task. One such feature is hashtags, which are user-defined topics.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba954a371bb18aca5b119fb1ffdaae57
https://doi.org/10.1007/978-3-319-24282-8_21
https://doi.org/10.1007/978-3-319-24282-8_21
Publikováno v:
International Journal of Pattern Recognition and Artificial Intelligence. 13:195-217
This paper addresses the problem of using domain generalization graphs to generalize temporal data extracted from relational databases. A domain generalization graph associated with an attribute defines a partial order which represents a set of gener
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::07b5e98894181d6c37d2b6502b127f5c
https://doi.org/10.1142/s0218001499000124
https://doi.org/10.1142/s0218001499000124
Publikováno v:
Journal of Intelligent Information Systems. 13:195-234
Attribute-oriented generalization summarizes the information in a relational database by repeatedly replacing specific attribute values with more general concepts according to user-defined concept hierarchies. We introduce domain generalization graph
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e3975fbea973b97a274cd8a9214c2ee
https://doi.org/10.1023/a:1008769516670
https://doi.org/10.1023/a:1008769516670
Publikováno v:
International Journal on Artificial Intelligence Tools. :189-220
We propose the share-confidence framework for knowledge discovery from databases which addresses the problem of mining characterized association rules from market basket data (i.e., itemsets). Our goal is to not only discover the buying patterns of c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4ac514a696d24186a51615e0540c9c7
https://doi.org/10.1142/s0218213098000111
https://doi.org/10.1142/s0218213098000111
Publikováno v:
IEEE Transactions on Software Engineering. 23:56-59
Regeneration with virtual copies (RVC) is a voting-based consistency control algorithm for replicated data objects in a distributed computing system. Proposed by Adam and Tewari (ibid., vol. 19, no. 6, pp. 594-602, 1993), it utilizes selective regene
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1579687257f776fa2864255abae8461e
https://doi.org/10.1109/32.581329
https://doi.org/10.1109/32.581329
Autor:
Garrett Nicolai, Robert J. Hilderman
Publikováno v:
Studies in Computational Intelligence ISBN: 9783642275333
IJCCI (Selected Papers)
IJCCI (Selected Papers)
No-Limit Texas Hold’em Poker is a stochastic game of imperfect information. Each player receives cards dealt randomly and does not know which cards his opponents have been dealt. These simple features result in No-Limit Texas Hold’em Poker having
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::32943ec003e836d847368caf0c04ac3e
https://doi.org/10.1007/978-3-642-27534-0_3
https://doi.org/10.1007/978-3-642-27534-0_3