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2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

作者： HONG LIU YUE-LIANG QIAN QUN LIU JIN-TAO LI Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080

Present elevator control use button sensors to determine when and where to dispatch an elevator car, which don't use the number of passengers. In this paper, we analyze images from camera to detect how many persons waiting for the elevator or in an elevator. A novel framework is proposed for optimized elevator schedule. Extended Haar-like features and Adaboost are used to train a head-shoulder classifier. Some images are selected from video according to elevator button callings to detect head-shoulder. To reduce false alarms a post process is added after detecting. Experimental results show the proposed method with post process has higher performance than existed methods. The information of passenger number can be send to elevator control system for effective schedule, which can reduce passengers waiting time and elevator's unnecessary stop, finally save energy and reduce maintain fee.

关键词： Elevator control system Haar-like features Adaboost Post process

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An Adaptive Travel Itinerary Selection Assistant under Fuzzy User Preferences

An Adaptive Travel Itinerary Selection Assistant under Fuzzy...

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2008 Conference on Human System Interactions (HSI 2008), vol.1

作者： Ruihong Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

This paper presents a candidate-evaluation model (CEM) which interactively elicits user preferences and assists decision makers in decision making in applications such as travel itinerary planning. The CEM contrasts with traditional decision analytic and planning frameworks in which a complete user model is elicited beforehand or is constructed by a human expert. We used the CEM model to implement an Itinerary Selection Assistant (ISA) system, which helps tourists identify satisfactory travel itineraries. The ISA starts with fuzzy user preferences and gradually approximate the optimal solution through carefully choosing candidate solutions to present to the user and inferring user's actual preferences by analyzing user evaluations over the candidates.

关键词： Augmented weighted Tchebycheff programming Fuzzy user preferences Multi-attribute decision making Travel itinerary User modeling

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The Maximum Entropy based Rule Selection Model for Statistical Machine Translation (Invited Paper)

The Maximum Entropy based Rule Selection Model for Statistic...

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International Symposium on Universal Communication, ISUC

作者： Qun Liu Zhongjun He Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

This paper presents a novel rule selection model for statistical machine translation (SMT) that uses the maximum entropy approach to predict target-side for an ambiguous source-side. The maximum entropy based rule selection (MERS) model combines rich contextual information as features, thus can help SMT systems perform context-dependent rule selection. We incorporate the MERS model into two kinds of the state-of-the-art syntax-based SMT models: the hierarchical phrase-based model and the tree-to-string alignment template model. Experiments show that our approach achieves significant improvements over both the baseline systems.

关键词： Entropy Surface-mount technology Helium Decoding Predictive models Context modeling Power generation economics Laboratories Machine intelligence information processing

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Focused Crawling with Heterogeneous Semantic information

Focused Crawling with Heterogeneous Semantic Information

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Rui Huang Fen Lin Zhongzhi Shi Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

Focused crawlers selectively retrieve Web documents that are relevant to a predefined set of topics. To intelligently make predictions and decisions about relevant URLs and web pages, different topic models have been introduced to represent topic-specific knowledge. Yet it is difficult to support semantic interoperability among different models. Moreover, some manually specified additional semantic information, such as semantic markups and social annotations, could not be effectively used to improve crawling. This paper proposes to boost focused crawling with four kinds of semantic models and semantic information, including thesauruses, categories, ontologies, and folksonomies. A statistical semantic association model is proposed to integrate different semantic models, represent heterogeneous semantic information, and support semantic relevance computation. A focused crawling framework is developed which adopts both keyword based contents and different kinds of additional information for relevance prediction and ranking. Experiments show that the proposed model and framework effectively integrates heterogeneous semantic information for focused crawling.

关键词： Crawlers Web pages Uniform resource locators intelligent agent Computers Ontologies information processing Semantic Web information retrieval Predictive models

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High performance word level sequential and parallel coding methods and architectures for bit plane coding

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Science in China(Series F) 2008年第4期51卷 337-351页

作者： XIONG ChengYi TIAN JinWen LIU Jian College of Electronic Information Engineering South-Central University for Nationalities Wuhan 430074 China Institute of Pattern Recognition & Artificial Intelligence Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan 430074 China

This paper introduced a novel high performance algorithm and VLSI architectures for achieving bit plane coding （BPC） in word level sequential and parallel mode. The proposed BPC algorithm adopts the techniques of coding pass prediction and parallel ＆ pipeline to reduce the number of accessing memory and to increase the ability of concurrently processing of the system, where all the coefficient bits of a code block could be coded by only one scan. A new parallel bit plane architecture （PA） was proposed to achieve word-level sequential coding. Moreover, an efficient high-speed architecture （HA） was presented to achieve multi-word parallel coding. Compared to the state of the art, the proposed PA could reduce the hardware cost more efficiently, though the throughput retains one coefficient coded per clock. While the proposed HA could perform coding for 4 coefficients belonging to a stripe column at one intra-clock cycle, so that coding for an NxN code-block could be completed in approximate N2/4 intra-clock cycles. Theoretical analysis and experimental results demonstrate that the proposed designs have high throughput rate with good performance in terms of speedup to cost, which can be good alternatives for low power applications.

关键词： bit plane coding high performance word-level sequential multi-word parallel

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New approach to heterogeneous semantic search on the web

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2008年第8期45卷 1338-1345页

作者： Huang, Rui Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China

Relevance ranking is a key to Web search in determining how results are retrieved and ordered. As keyword-based search does not guarantee relevance in meanings, semantic search has been put forward as an attractive and promising approach. Recently several kinds of semantic information have been adopted in search respectively, such as thesauruses, ontologies and semantic markups, as well as folksonomies and social annotations. However, although to integrate more semantics would logically generate better search results, search mechanism to fully adopt different kinds of semantic information is still in absence and to be researched. To these ends, an integrated semantic search mechanism is proposed to incorporate textual information and keyword search with heterogeneous semantic information and semantic search. A statistical based measurement of semantic relevance, defined as semantic probabilities, is introduced to integrate both keywords and four kinds of semantic information including thesauruses, categories, ontologies and folksonomies. It is calculated with all textual information and semantic information, and stored in a newly proposed index structure called semantic-keyword dual index. Based on this uniform measurement, the search mechanism is developed that fully utilizes existing keyword and semantic search mechanisms to enhance heterogeneous semantic search. Experiments show that the proposed approach can effectively integrate both keyword-based information and heterogeneous semantic information in search.

关键词： Semantic Web

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Survey of semantic mapping in image retrieval

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Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics 2008年第8期20卷 1085-1096页

作者： Li, Zhixin Shi, Zhiping Li, Zhiqing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China

Semantic gap has become a bottleneck of content-based image retrieval. In order to bridge the gap and improve retrieval accuracy, a map from lower-level visual features to high-level semantics should be formulated. This paper provides a comprehensive survey on semantic mapping. Firstly, an image retrieval framework integrated with high-level semantics is presented. Secondly, image semantic description is introduced in two aspects: image content level-models and semantic representations. Thirdly, as the emphasis of this paper, semantic mapping approaches and techniques are investigated by classifying them into four main categories in terms of their characteristics. Various ideas and models proposed in these approaches are analyzed. In addition, advantages and limitations of each category are discussed. Finally, based on the state-of-the-art technology and the demand from real-world applications, several important issues related to semantic image retrieval are identified and some promising research directions are suggested.

关键词： Image annotation

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Convergence property analysis for PSO based on cluster-degree

Convergence property analysis for PSO based on cluster-degre...

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2008 International Conference on Computational Intelligence and Security, CIS 2008

作者： Quansheng, Dou Zhijun, Yu Ping, Jiang Zhongzhi, Shi Yantai Dongfang Electronics Information Industry Group Co. Ltd. Yantai China School of Nursing Binzhou Medical University Yantai China School of Computer Science and Technology Shandong Institute of Business and Technology Yantai China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769535081

The concept of cluster-degree was put forward and distribute status of particle with different clusterdegree was studied. The reasonable parameters setting range based on cluster-degree was proposed. Under the direction of cluster-degree, many parameters which can get better searching results were found. So this paper is helpful for the choosing and adjustment of PSO parameters in practical application. © 2008 IEEE.

关键词： Convergence Computational intelligence Computer security information security information analysis Industrial electronics Computer industry Electronics industry Medical services Computer science

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A novel fuzzy likelihood measure algorithm

A novel fuzzy likelihood measure algorithm

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International Conference on Computer Science and Software Engineering, CSSE 2008

作者： Ding, Shifei Jin, Fengxiang School of Computer Science and Technology China University of Mining and Technology Xuzhou 221008 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing 100080 China College of Geoinformation Science and Engineering Shandong University of Science and Technology Qingdao 266510 China

ISBN: (纸本)9780769533360

Similarity Measure(PSM) is a kind of measurement that measure the size of similarity between two patterns, it plays a key role in the analysis and research of pattern recognition, machine learning, clustering analysis. This article will firstly study the current PSM theory, point out its application range;secondly, discuss the axiomatic theory of fuzzy likelihood measure, give the frequently-used algorithms of fuzzy likelihood measure that based on axiomatic theory;finally, advance a new kind of fuzzy likelihood function, then establish the Fuzzy Likelihood Measure(FLM) between two fuzzy sets, so as to describe the similar degree between two fuzzy sets. FLM theory not only enriches and improves the PLS theory, and also provides new research methods for the theory research such as pattern recognition, machine learning, clustering analysis and so on. © 2008 IEEE.

关键词： Fuzzy sets

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Point based large-scale crowds real-time 3D visualization method

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2008年第10期45卷 1731-1738页

作者： Shu, Bo Mao, Tianlu Xu, Wenbin Wang, Zhaoqi Virtual Reality Laboratory Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China

3D visualization of large-scale virtual crowds is a very important and interesting problem in research fields of virtual reality. For reasons of efficiency and visual realism, it is very difficult to populate, animate and render large-scale virtual crowds with hundreds of thousand individually animated virtual characters in real-time applications;especially for the scene which has more than ten thousands of individuals with different shapes and motions. In this paper, an efficient method to visualize large-scale virtual crowds is presented. Firstly, using model variation technique, many different models can be derived from a small number of model templates. Secondly, the crowds can be animated individually by deforming a small number of elements in motion database. Thirdly, using a developed point sample rendering algorithm, large-scale crowds can be displayed in real-time. This method can be used to visualize different dynamic crowds which require both real-time efficiency and large number of virtual individuals support. Based on this work, an efficient and readily usable 3D visualization system is presented. It can provide very high visual realism for large crowds' visualization in interactive frame rates on a regular PC. The 3D visualization of 60000 people evacuating from a building is also realized in real-time based on the system.

关键词： Virtual reality

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