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Top-k entities query processing on uncertainly fused multi-sensory data

PERSONAL AND UBIQUITOUS COMPUTING 2013年第5期17卷 951-963页

作者： Liu, Dexi Wan, Changxuan Xiong, Naixue Park, Jong Hyuk Rho, Seungmin Jiangxi Univ Finance & Econ Sch Informat Technol Jiangxi Key Lab Data & Knowledge Engn Nanchang Peoples R China Georgia State Univ Dept Comp Sci Atlanta GA 30303 USA Seoul Natl Univ Sci & Technol Dept Comp Sci & Engn Seoul South Korea Korea Univ Sch Elect Engn Seoul South Korea

Sensor fusion is the combining of sensory data from disparate sources such that the resulting information is in some sense better than would be possible when these sources were used individually. The natural uncertainty exists in these data because sensors are not precise enough. Hence, the intuitive method to store this kind of data is using uncertain database. Finding the top-k entities according to one or more attributes is a powerful technique when the uncertain database contains large quantity of data. However, compared to top-k in traditional databases, queries over uncertain database are more complicated because of the existence of exponential possible worlds. We propose a method to process entity-based global top-k aggregate queries in uncertain database, which returns the top-k entities that have the highest aggregate value. Our method has two levels, entity state generation and G-topk-E query processing. In the former level, entity states, which satisfy the properties of x-tuple, are generated one after the other according to their aggregate values, while in the latter level, dynamic programming-based global top-k entity query processing is employed to return the answers. Comprehensive experiments on different data sets demonstrate the effectiveness of the proposed solutions.

关键词： G-topk-E-Agg query e-Tuple, dynamic programming algorithm Uncertain database Multi-sensory data

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Top-k entities query processing on uncertainly fused multi-sensory data

Top-k entities query processing on uncertainly fused multi-s...

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作者： Liu, Dexi Wan, Changxuan Xiong, Naixue Park, Jong Hyuk Rho, Seungmin Jiangxi Key Laboratory of Data and Knowledge Engineering School of Information Technology Jiangxi University of Finance and Economics Nanchang China Department of Computer Science Georgia State University Atlanta GA United States Department of Computer Science and Engineering Seoul National University of Science and Technology Seoul Korea Republic of School of Electrical Engineering Korea University Seoul Korea Republic of

关键词： Query processing

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Synonyms weighted LDA for product aspects extraction

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International Journal of Applied Mathematics and Statistics 2013年第24期51卷 283-291页

作者： Peng, Yun Wan, Changxuan School of Information and Technology Jiangxi University of Finance and Economics Nanchang 330013 Jiangxi China Computer and Information Engineering College Jiangxi Normal University Nanchang 330022 Jiangxi China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang 330013 Jiangxi China

It is important to extract the aspects from the comments of shoppers about certain products. Product aspect descriptions often contain words of same meaning, and discriminating these synonyms effectively can improve the efficiency of aspects extraction. Standard topic model in identifying those words, because of the absent introduction of priori knowledge, will largely ignore the relations of words meaning. An improved aspects extracting model of LDA by adding synonymous words constraint is proposed in this paper. In the process of words clustering analysis, words with high similarity are aggregated in the same cluster. In the stage of aspects extraction, we introduce words clustering and cluster membership weights as priori knowledge to strengthen the original LDA topic model for features clustering, which can improve the accuracy of product aspects extraction. Our experiments show that synonyms weighted LDA proposed in this paper outperforms the original LDA by a large margin. © 2013 by CESER Publications.

关键词： Extraction

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A new BP algorithm for network marketing performance evaluation of agricultural products

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Journal of Applied Sciences 2013年第20期13卷 4332-4335页

作者： Zou, Chun-Fang Huang, Li-Juan School of of Business Administration Jiangxi University of Finance and Economics 330013 Nanchang Jiangxi China School of Information Technology Jiangxi University of Finance and Economics 330013 Nanchang Jiangxi China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics 330013 Nanchang Jiangxi China

Network marketing performance evaluation can sum up and improve the network marketing activities for network enterprises. So, how to evaluate network marketing performance has become a matter of concern in the field related. The study mainly takes agricultural products for example and presents a new algorithm for evaluating network marketing performance based on improved BP neural network algorithm. First, a evaluation indicator system for evaluating network marketing performance of agricultural products is constructed;Second the study analyzes the reasons of the defects of BP neural network algorithm and then designs a new BP algorithm and improves it through changing its learning rate to speed up the calculation and simplify the structure of the original BP algorithm;Finally, the improved algorithm is realized with three e_commerce enterprises are taken for examples to evaluate the network marketing performance and verify the validity and feasibility of the model and the experimental results show that the model can evaluate the network marketing performance of different enterprises practically. © 2013 Asian Network for Scientific Information.

关键词： Agricultural products

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JUFE at INEX 2011 Snippet Retrieval Track

JUFE at INEX 2011 Snippet Retrieval Track

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Lecture Notes in Computer Science

作者： Liu, Dexi Wan, Changxuan Liao, Guoqiong Zhong, Minjuan Liu, Xiping School of Information Technology Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9783642357336

jiangxi University of Finance and Economics (JUFE) submitted 8 runs to the Snippet Retrieval Track at INEX *** report describes an XML snippet retrieval method based on Average Topic Generalization (ATG) model used by JUFE. The basic idea of the ATG is that different element in an XML document plays different role and hence should has distinguishing importance. The ATG model sets a weight automatically to each element according to its tag or path in the XML document. Then, the BM25EW model based on the ATG is proposed to retrieve and rank the relevant elements in an XML document collection. All windows in the most relevant elements are scored and those windows with higher scores are extracted as snippets. By comparing with the runs under different strategies, the performance are discussed and analyzed in detail. © Springer-Verlag Berlin Heidelberg 2012.

关键词： XML

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Research on XML element search results clustering

Research on XML element search results clustering

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6th International Conference on Management of e-Commerce and e-Government, ICMeCG 2012

作者： Zhong, Min-Juan Wan, Chang-Xuan Liu, De-Xi Jiao, Xian-Pei School of Information Technology Jiangxi University of Finance and Economics Nanchang China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9781467329439

Clustering XML search results is an effective way to improve performance. However, the key problem is how to measure similarity between XML documents. This paper studies XML search results clustering based on element granularity and proposes one similarity measurement method. The method firstly uses latent semantic indexing technology(LSI) to obtain term semantics and then combines the XML element node content and semantic structure properties(CASS). To evaluate clustering performance, two new performance evaluation methodologies, namely R-ClusterRatio and R-DocuRatio are introduced. It is motivated by the observations of relevant documents distribution and the fact that the experiment data collection, IEEE CS corpus, do not provide classification information. Experiment results show that proposed similarity method combining term semantics with content and structure semantics integration(LSI-CASS) is feasible, and it produces better clustering quality than LSI-CAS. © 2012 IEEE.

关键词： Semantics

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Fusing heterogeneous information for social image retrieval

Fusing heterogeneous information for social image retrieval

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Int. Workshops on Web-Age Information Management, WAIM 2012: 1st Int. Workshop on GDMM 2012, 2nd Int. Wireless Sensor Networks Workshop, IWSN 2012, 1st Int. Workshop on MDSP 2012, 3rd Int. Workshop on USDM 2012, 4th Int. Workshop on XMLDM 2012

作者： Li, Xirong MOE Key Lab. of Data Engineering and Knowledge Engineering Renmin University of China China

ISBN: (纸本)9783642330490

Given that millions of images are uploaded to the social web in a single day, how to effectively retrieve such increasing amounts of unstructured data becomes crucial. While current social platforms find images on the base of user-contributed tags, the tags are known to be subjective and noisy, and consequently put the effectiveness of social image retrieval into question. Different from existing work which focuses on analyzing individual sources of information such as textual and visual separately, in this paper we propose to fuse the heterogeneous information. We investigate the state of the art weighting methods within a linear fusion framework. Image retrieval experiments on a present day benchmark with 46 visual concept queries show encouraging results. Compared to the best search results obtained by a single source of information, the Uniform method and the Coordinate Ascent method obtain relative performance gain of 3.9% and 5.7% in terms of mean average precision. This work provides some practical guidelines for fusing multiple sources of information for improving social image retrieval. © 2012 Springer-Verlag.

关键词： Image enhancement

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RUC @ INEX 2011 data-centric track

RUC @ INEX 2011 data-centric track

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Lecture Notes in Computer Science

作者： Wang, Qiuyue Gan, Yantao Sun, Yu School of Information Renmin University of China China Key Lab. of Data Engineering and Knowledge Engineering MOE Beijing 100872 China

ISBN: (纸本)9783642357336

We report our experiment results on the INEX 2011 data-Centric Track. We participated in both the ad hoc and faceted search tasks. On the ad hoc search task, we employ language modeling approaches to do structured object retrieval, trying to capture both the structure in data and structure in query and unify the structured and unstructured information retrieval in a general framework. However, our initial experimental results using INEX test bed show that the unstructured retrieval model performs better than structured retrieval models. On the faceted search task, we propose a simple user-simulation model to evaluate the effectiveness of a faceted search system's recommending facet-values. We implemented the evaluation system and conducted the evaluations for the track. We also tested basic redundancy and relevance based approaches for recommending facet-values. The results show that our basic approaches of recommending facet-values perform quite well. © Springer-Verlag 2012.

关键词： XML

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Integrated retrieval over structured and unstructured data

Integrated retrieval over structured and unstructured data

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2012 Cross Language Evaluation Forum Conference, CLEF 2012

作者： Wang, Qiuyue Kang, Jinglin School of Information Renmin University of China Beijing100872 China Key Lab of Data Engineering and Knowledge Engineering MOE Beijing100872 China

We report our experiment results on the INEX 2012 Linked data Track. We participated in the ad hoc and jeopardy tasks. As the new data collection on INEX 2012 Linked data Track features a combination of unstructured and structured data, our first attempt is to investigate different strategies of combining the retrievals over structured and unstructured data, and compare the combined approaches with the traditional unstructured ones. In this paper, we discussed three types of combination strategies and we experimented two of them on the track. The experiment results show that.

关键词： Linked data

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Fusing concept detection and geo context for visual search 12

Fusing concept detection and geo context for visual search

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2nd ACM International Conference on Multimedia Retrieval, ICMR 2012

作者： Li, Xirong Snoek, Cees G.M. Worring, Marcel Smeulders, Arnold W.M. MOE Key Lab of Data Engineering and Knowledge Engineering Renmin University of China China Intelligent Systems Lab Amsterdam University of Amsterdam Netherlands Centrum Wiskunde and Informatica Netherlands

ISBN: (纸本)9781450313292

Given the proliferation of geo-tagged images, the question of how to exploit geo tags and the underlying geo context for visual search is emerging. Based on the observation that the importance of geo context varies over concepts, we propose a concept-based image search engine which fuses visual concept detection and geo context in a concept-dependent manner. Compared to individual content-based and geo-based concept detectors and their uniform combination, concept-dependent fusion shows improvements. Moreover, since the proposed search engine is trained on social-tagged images alone without the need of human interaction, it is flexible to cope with many concepts. Search experiments on 101 popular visual concepts justify the viability of the proposed solution. In particular, for 79 out of the 101 concepts, the learned weights yield improvements over the uniform weights, with a relative gain of at least 5% in terms of average precision. Copyright © 2012 ACM.

关键词： Search engines

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