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Artificial Intelligence And Information-control Systems Of Robots '97 - Proceedings Of The Seventh International Conference
AIICSR '97 (Artificial Intelligence and Information-Control Systems of Robots) is one of the most traditional East-West professional meetings devoted to artifical intelligence (AI) and its applications in robots. The themes of the conference are aimed at the issues of AI theory and applications. The conference is devoted to the development and philosophical reflections of AI, and presents the most important topics, such as knowledge discovery and data mining, and study of context. In addition to robots, AI has created softbots — software robots working in a complex information environment. The WWW has become the most exciting application of AI. Further important topics in this volume include formal modelling of reactive systems, development of parallel and distributed computer architectures, declarative programming, agent societies and other fields, from which theoretical results in computer vision and its applications in robotics deserve special attention.
Advances in Information Retrieval
This book constitutes the refereed proceedings of the 30th annual European Conference on Information Retrieval Research, ECIR 2009, held in Toulouse, France in April 2009. The 42 revised full papers and 18 revised short papers presented together with the abstracts of 3 invited lectures and 25 poster papers were carefully reviewed and selected from 188 submissions. The papers are organized in topical sections on retrieval model, collaborative IR / filtering, learning, multimedia - metadata, expert search - advertising, evaluation, opinion detection, web IR, representation, clustering / categorization as well as distributed IR.
String Processing and Information Retrieval
This book constitutes the refereed proceedings of the 13th International Conference on String Processing and Information Retrieval, SPIRE 2006. The 26 revised full papers and 5 revised short papers presented together with 2 invited talks were carefully reviewed and selected. The papers are organized in topical sections on Web clustering and text categorisation, strings, user behaviour, Web search algorithms, compression, correction, information retrieval applications, bio-informatics, and Web search engines.
Opinions, Sentiment, and Emotion in Text
This book gives a comprehensive introduction to all the core areas and many emerging themes of sentiment analysis.
Sentiment Analysis and Opinion Mining
Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have...
Sentiment Analysis
A comprehensive introduction to computational analysis of sentiments, opinions, emotions, and moods. Now including deep learning methods.
Industrial Engineering, Computation and Information Technologies
Selected, peer reviewed papers from the 2014 2nd International Conference on Mechatronics and Information Technology (ICMIT 2014), October 18-19, 2014, Chongqing, China
Temporal Pattern Mining in Dynamic Environments
Many domains feature a dynamic characteristic like logistics, sports, or medicine and it would be useful to learn about frequent patterns, e.g., in what situations a traffic jam is likely to happen. Additionally, we are facing complex situations with many objects and relations that might change over time. The learning approach developed in this work identifies frequent temporal patterns out of qualitative, interval-based descriptions of dynamic scenes by extending the Apriori algorithm and combining ideas from relational as well as sequential association rule mining approaches. Temporal relations in patterns are represented by qualitative interval relations as they have been introduced by Allen and Freksa. The search for frequent patterns is a top-down approach starting by the most general (empty) pattern and performing specialization steps by applying an optimal refinement operator. In a second step, prediction rules are generated by splitting the identified patterns into precondition and consequence parts. The developed concepts are implemented in the MiTemP system and are evaluated on synthetic data and soccer matches of the RoboCup simulation league.
