Results 1 - 10 of 21,168

Combining search-based procedural content generation and social gaming in the petalz video game

by Sebastian Risi, Joel Lehman, David B. D’ambrosio, Ryan Hall, Kenneth O. Stanley - in 8th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment , 2012
"... Search-based procedural content generation methods allow video games to introduce new content continually, thereby engaging the player for a longer time while reducing the burden on developers. However, games so far have not explored the potential economic value of unique evolved artifacts. Building ..."
Abstract - Cited by 14 (8 self) - Add to MetaCart
Search-based procedural content generation methods allow video games to introduce new content continually, thereby engaging the player for a longer time while reducing the burden on developers. However, games so far have not explored the potential economic value of unique evolved artifacts

Three approaches to qualitative content analysis.

by Hsiu-Fang Hsieh , Sarah E Shannon , 2005
"... Content analysis is a widely used qualitative Researchers regard content analysis as a flexible method for analyzing text data The differentiation of content analysis is usually limited to classifying it as primarily a qualitative versus quantitative research method. A more thorough analysis of th ..."
Abstract - Cited by 729 (0 self) - Add to MetaCart
and support in writing this article. QUALITATIVE HEALTH RESEARCH, Vol. 15 No. 9, November 2005 1277-1288 DOI: 10.1177/1049732305276687 © 2005 use content analysis and the analytic procedures employed in such studies, thus avoiding a muddling of methods Our purpose in this article is to present the breadth

Discrete Choice Methods with Simulation

by Kenneth E. Train , 2002
"... This book describes the new generation of discrete choice meth-ods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logi ..."
Abstract - Cited by 1326 (20 self) - Add to MetaCart
This book describes the new generation of discrete choice meth-ods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered

A New Method for Solving Hard Satisfiability Problems

by Bart Selman, Hector Levesque, David Mitchell - AAAI , 1992
"... We introduce a greedy local search procedure called GSAT for solving propositional satisfiability problems. Our experiments show that this procedure can be used to solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional approac ..."
Abstract - Cited by 730 (21 self) - Add to MetaCart
We introduce a greedy local search procedure called GSAT for solving propositional satisfiability problems. Our experiments show that this procedure can be used to solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional

Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach

by Jiawei Han, Jian Pei, Yiwen Yin, Runying Mao - DATA MINING AND KNOWLEDGE DISCOVERY , 2004
"... Mining frequent patterns in transaction databases, time-series databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still co ..."
Abstract - Cited by 1752 (64 self) - Add to MetaCart
FP-tree-based mining adopts a pattern-fragment growth method to avoid the costly generation of a large number of candidate sets, and (3) a partitioning-based, divide-and-conquer method is used to decompose the mining task into a set of smaller tasks for mining confined patterns in conditional

Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions

by Gediminas Adomavicius, Alexander Tuzhilin - IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING , 2005
"... This paper presents an overview of the field of recommender systems and describes the current generation of recommendation methods that are usually classified into the following three main categories: content-based, collaborative, and hybrid recommendation approaches. This paper also describes vario ..."
Abstract - Cited by 1490 (23 self) - Add to MetaCart
This paper presents an overview of the field of recommender systems and describes the current generation of recommendation methods that are usually classified into the following three main categories: content-based, collaborative, and hybrid recommendation approaches. This paper also describes

TABU SEARCH

by Fred Glover, Rafael Marti
"... Tabu Search is a metaheuristic that guides a local heuristic search procedure to explore the solution space beyond local optimality. One of the main components of tabu search is its use of adaptive memory, which creates a more flexible search behavior. Memory based strategies are therefore the hallm ..."
Abstract - Cited by 822 (48 self) - Add to MetaCart
Tabu Search is a metaheuristic that guides a local heuristic search procedure to explore the solution space beyond local optimality. One of the main components of tabu search is its use of adaptive memory, which creates a more flexible search behavior. Memory based strategies are therefore

Model-Based Clustering, Discriminant Analysis, and Density Estimation

by Chris Fraley, Adrian E. Raftery - JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION , 2000
"... Cluster analysis is the automated search for groups of related observations in a data set. Most clustering done in practice is based largely on heuristic but intuitively reasonable procedures and most clustering methods available in commercial software are also of this type. However, there is little ..."
Abstract - Cited by 573 (29 self) - Add to MetaCart
Cluster analysis is the automated search for groups of related observations in a data set. Most clustering done in practice is based largely on heuristic but intuitively reasonable procedures and most clustering methods available in commercial software are also of this type. However

SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries

by James Z. Wang, Jia Li, Gio Wiederhold - IEEE Transactions on Pattern Analysis and Machine Intelligence , 2001
"... The need for efficient content-based image retrieval has increased tremendously in many application areas such as biomedicine, military, commerce, education, and Web image classification and searching. We present here SIMPLIcity (Semanticssensitive Integrated Matching for Picture LIbraries), an imag ..."
Abstract - Cited by 551 (35 self) - Add to MetaCart
The need for efficient content-based image retrieval has increased tremendously in many application areas such as biomedicine, military, commerce, education, and Web image classification and searching. We present here SIMPLIcity (Semanticssensitive Integrated Matching for Picture LIbraries

Symbolic Model Checking without BDDs

by Armin Biere , Alessandro Cimatti, Edmund Clarke, Yunshan Zhu , 1999
"... Symbolic Model Checking [3, 14] has proven to be a powerful technique for the verification of reactive systems. BDDs [2] have traditionally been used as a symbolic representation of the system. In this paper we show how boolean decision procedures, like Stalmarck's Method [16] or the Davis ..."
Abstract - Cited by 917 (75 self) - Add to MetaCart
Symbolic Model Checking [3, 14] has proven to be a powerful technique for the verification of reactive systems. BDDs [2] have traditionally been used as a symbolic representation of the system. In this paper we show how boolean decision procedures, like Stalmarck's Method [16] or the Davis
Results 1 - 10 of 21,168