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» Evaluating algorithms that learn from data streams
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VALUETOOLS
2006
ACM
164views Hardware» more  VALUETOOLS 2006»
16 years 1 months ago
Analysis of Markov reward models using zero-suppressed multi-terminal BDDs
High-level stochastic description methods such as stochastic Petri nets, stochastic UML statecharts etc., together with specifications of performance variables (PVs), enable a co...
Kai Lampka, Markus Siegle
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
16 years 7 months ago
Scalable pseudo-likelihood estimation in hybrid random fields
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Antonino Freno, Edmondo Trentin, Marco Gori
EPIA
2005
Springer
16 years 24 days ago
Improving Passage Retrieval in Question Answering Using NLP
Abstract. This paper describes an approach for the integration of linguistic information in passage retrieval in an open-source question answering system for Dutch. Annotation prod...
Jörg Tiedemann
DEBS
2010
ACM
15 years 2 months ago
Distributed structural and value XML filtering
Many XML filtering systems have emerged in recent years identifying XML data that structurally match XPath queries in an efficient way. However, apart from structural matching, it...
Iris Miliaraki, Manolis Koubarakis
ICDM
2010
IEEE
267views Data Mining» more  ICDM 2010»
15 years 5 months ago
Personalizing Web Page Recommendation via Collaborative Filtering and Topic-Aware Markov Model
Web-page recommendation is to predict the next request of pages that Web users are potentially interested in when surfing the Web. This technique can guide Web users to find more u...
Qingyan Yang, Ju Fan, Jianyong Wang, Lizhu Zhou