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rHDP: An Aspect Sharing-Enhanced Hierarchical Topic Model for Multi-Domain Corpus

ACM TRANSACTIONS ON INFORMATION SYSTEMS 2024年第3期42卷 1-31页

作者： Zhang, Yitao Wan, Changxuan Xiao, Keli Wan, Qizhi Liu, Dexi Liu, Xiping Jiangxi Univ Finance & Econ Nanchang Peoples R China East China Jiaotong Univ Nanchang Peoples R China Jiangxi Key Lab Data & Knowledge Engn Nanchang Peoples R China SUNY Stony Brook Coll Business New York NY USA

Learning topic hierarchies from a multi-domain corpus is crucial in topic modeling as it reveals valuable structural information embedded within documents. Despite the extensive literature on hierarchical topic models, effectively discovering inter-topic correlations and differences among subtopics at the same level in the topic hierarchy, obtained from multiple domains, remains an unresolved challenge. This article proposes an enhanced nested Chinese restaurant process (nCRP), nCRP+, by introducing an additional mechanism based on Chinese restaurant franchise (CRF) for aspect-sharing pattern extraction in the original nCRP. Subsequently, by employing the distribution extracted from nCRP+ as the prior distribution for topic hierarchy in the hierarchical Dirichlet processes (HDP), we develop a hierarchical topic model for multi-domain corpus, named rHDP. We describe the model with the analogy of Chinese restaurant franchise based on the central kitchen and propose a hierarchical Gibbs sampling scheme to infer the model. Our method effectively constructs well-established topic hierarchies, accurately reflecting diverse parent-child topic relationships, explicit topic aspect sharing correlations for inter-topics, and differences between these shared topics. To validate the efficacy of our approach, we conduct experiments using a renowned public dataset and an online collection of Chinese financial documents. The experimental results confirm the superiority of our method over the state-of-the-art techniques in identifying multi-domain topic hierarchies, according to multiple evaluation metrics.

关键词： Hierarchical topic model aspect sharing pattern Chinese restaurant franchise hierarchical Dirichlet processes

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XRCJ: Supporting keyword search in XML and relation co-occurrence

XRCJ: Supporting keyword search in XML and relation co-occur...

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1st International Workshop on Graph database, IWGD 2010, 1st International Workshop on Advanced Techniques on XML data Management, XMLDM 2010, 2nd International Workshop on WCMT 2010, Held in Conj. with WAIM 2010

作者： Zhang, Song Du, Xiaoyong Key Lab. of Data Engineering and Knowledge Engineering School of Information Renmin University of China China

ISBN: (纸本)3642167195

keyword search is a proven, user-friendly way to query html documents in the World Wide Web. With the trend of integrating IR technologies into DB community, state-of-the-art studies have introduced keyword search into XML and relation. In this paper we introduce keyword search into a new circumstance called XRC (XML and relation co-occurrence) where XML and relational data exist at the same storage. By exploring semantic relationships between data from relation and XML, we enable users who intend to visit data from XML and relation to access information in an easier manner. To achieve this target, we propose a novel operation called XRCJ which connects data from XML and relation together when answering search query. We also improve traditional inverted index and design a mixed inverted index. Through conducting extensive experiments on synthetic data from real data set DBLP, we find that our method can achieve a good performance in XML and relation co-occurrence circumstance. © 2010 Springer-Verlag.

关键词： XML

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A Novel Storage Architecture of In-Memory databases Supporting Real-time E-commerce Applications

A Novel Storage Architecture of In-Memory Databases Supporti...

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2nd International Conference on Management of e-Commerce and e-Government

作者： Deng Kun Liao Guoqiong Huang Yukun Li Jing Xia Jiali Jiangxi Univ Finance & Econ Sch Informat Technol Nanchang 330013 Peoples R China Jiangxi Univ Finance & Econ Jiangxi Key Lab Data & Knowledge Engn Nanchang 330013 Jiangxi Peoples R China Jiangxi Univ Finance & Econ Sch Software Nanchang 330013 Jiangxi Peoples R China

ISBN: (纸本)9780769533667

With growing numbers of suppliers/buyers and the introduction of new additional applications, the simplified and centralized organization of data in the E-commerce systems becomes a focus in reducing operational and capital expenses. With the availability of faster server hardware, network connections and high performance databases, the realization of a common database hosting data for multiple applications becomes technically feasible. However, this kind of deployment will bring new challenges to database systems. One critical challenge is the database should be optimized for real-time accessing databases on large data size. In this report, a novel main memory database architecture based on solid state disks is suggested to meet the requirement. Experiment results shows following benefits can be obtained from the solid state disks: transaction throughput, average response time of write transactions, and database recovery time.

关键词： Memory architecture database data size electronic commerce database systems solid state database recovery Reaction Time solid-state disk disks cultivators deployment database architecture

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Weighting tags and paths in XML documents according to their topic generalization

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INFORMATION SCIENCES 2013年 249卷 48-66页

作者： Liu, Dexi Wan, Changxuan Chen, Lei Liu, Xiping Nie, Jian-Yun Jiangxi Univ Finance & Econ Nanchang 330013 Peoples R China Jiangxi Key Lab Data & Knowledge Engn Nanchang Peoples R China Hong Kong Univ Sci & Technol Hong Kong Hong Kong Peoples R China Univ Montreal Montreal PQ Canada

Text-centric (or document-centric) XML document retrieval aims to rank search results according to their relevance to a given query. To do this, most existing methods mainly rely on content terms and often ignore an important factor - the XML tags and paths, which are useful in determining the important contents of a document. In some previous studies, each unique tag/path is assigned a weight based on domain (expert) knowledge. However, such a manual assignment is both inefficient and subjective. In this paper, we propose an automatic method to infer the weights of tags/paths according to the topical relationship between the corresponding elements and the whole documents. The more the corresponding element can generalize the document's topic, the more the tag/path is considered to be important. We define a model based on Average Topic Generalization (ATG), which integrates several features used in previous studies. We evaluate the performance of the ATG-based model on two real data sets, the IEEECS collection and the Wikipedia collection, from two different perspectives: the correlation between the weights generated by ATG and those set by experts, and the performance of XML retrieval based on ATG. Experimental results show that the tag/path weights generated by ATG are highly correlated with the manually assigned weights, and the ATG model significantly improves XML retrieval effectiveness. (C) 2013 Elsevier Inc. All rights reserved.

关键词： XML retrieval Tag/path weighting model Topic generalization

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Token-Event-Role Structure-Based Multi-Channel Document-Level Event Extraction

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ACM TRANSACTIONS ON INFORMATION SYSTEMS 2024年第4期42卷 1-27页

作者： Wan, Qizhi Wan, Changxuan Xiao, Keli Xiong, Hui Liu, Dexi Liu, Xiping Hu, Rong Jiangxi Univ Finance & Econ Sch Informat Management Nanchang Jiangxi Peoples R China Jiangxi Key Lab Data & Knowledge Engn Nanchang Jiangxi Peoples R China SUNY Stony Brook Coll Business Stony Brook NY USA Hong Kong Univ Sci & Technol Guangzhou Thrust Artificial Intelligence Guangzhou Guangdong Peoples R China

Document-level event extraction is a long-standing challenging information retrieval problem involving a sequence of sub-tasks: entity extraction, event type judgment, and event type-specific multi-event extraction. However, addressing the problem as multiple learning tasks leads to increased model complexity. Also, existing methods insufficiently utilize the correlation of entities crossing different events, resulting in limited event extraction performance. This article introduces a novel framework for document-level event extraction, incorporating a newdata structure called token-event-role and a multi-channel argument role predictionmodule. The proposed data structure enables our model to uncover the primary role of tokens in multiple events, facilitating a more comprehensive understanding of event relationships. By leveraging the multi-channel prediction module, we transform entity and multi-event extraction into a single task of predicting token-event pairs, thereby reducing the overall parameter size and enhancing model efficiency. The results demonstrate that our approach outperforms the state-of-the-art method by 9.5 percentage points in terms of the F1 score, highlighting its superior performance in event extraction. Furthermore, an ablation study confirms the significant value of the proposed data structure in improving event extraction tasks, further validating its importance in enhancing the overall performance of the framework

关键词： Document-level event extraction token-event-role data structure joint learning multi-channel neural network

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Filtering Redundant RFID data Based on Sliding Windows 8

Filtering Redundant RFID Data Based on Sliding Windows

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International Conference on Management of e-Commerce and e-Government (ICMeCG)

作者： Wu Rui Liao Guoqiong Di Guoqiang Jiangxi Univ Finance & Econ Sch Informat Technol Nanchang Peoples R China Jiangxi Univ Finance & Econ Sch Informat Technol Jiangxi Key Lab Data & Knowledge Engn Nanchang Peoples R China

ISBN: (纸本)9781479965434

Filtering redundancy data is an important task of radio frequency identification (RFID) middleware. In order to ensure RFID middleware can effectively filter the time redundant data and identify tagged object location change timely, this paper proposed a Temporal-Spatial bloom filter based on the sliding window model. The filter extends the one-dimension array in the standard bloom filter to a two-dimension array. Meanwhile, in order to guarantee the false positive rate doesn't increase due to the reason that the storage unit of the filter becomes full, we proposed a random decay strategy for deleting the expiration elements. The experimental results show that TSBF algorithm can filter time redundant data effectively and had a good performance to deal with location movement.

关键词： RFID data Stream data Filtering Bloom Filter

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Efficient processing of global Top-k aggregate queries in uncertain database

Efficient processing of global Top-k aggregate queries in un...

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2009 International Conference on Information engineering and Computer Science, ICIECS 2009

作者： Xing, Xianli Liu, Dexi Principal's Office Jiangxi University of Finance and Economics Nanchang China School of Information Technology Jiangxi University of Finance and Economics Jiangxi Key Laboratory of Data and Knowledge Engineering Nanchang China

ISBN: (纸本)9781424449941

Top-k queries in uncertain databases are quite popular and useful due to its wide application usage. However, compared to Top-k in traditional databases, queries over uncertain database are more complicated because of the existence of exponential possible worlds. A Top-k aggregate query ranks groups of tuples by their aggregate values, sum or average for example, and returns k groups with the highest aggregate values. As a powerful semantic of Top-k, Global Top-k, returns k highest-ranked tuples according to their probabilities of being in the Top-k answers in possible worlds. We propose a dynamic programming based method to process Global Top-k aggregate queries in uncertain database, where the number of retrieved tuples and group states generated on these tuples are minimized. Experiment results show that our algorithm is effective. ©2009 IEEE.

关键词： Dynamic programming

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A query-oriented summarization system for XML elements

A query-oriented summarization system for XML elements

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2011 International Conference on Management of e-Commerce and e-Government, ICMeCG 2011

作者： Liu, Dexi Wu, Shihan Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang 330013 China Songjiang Branch Shanghai Rural Commercial Bank Shanghai 201600 China

ISBN: (纸本)9780769545448

In document-center XML dataset, an element may contain so many text that users have to spend enough time to judge the elements returned by XML search engine are valuable or not. Query-orient XML summarization system aim to provide users a brief and readable substitution of the original retrieved elements according to the user's query, which can relieve user's reading burden effectively. In this work, we extract sentences from the results of XML search engine, and combine them as a summary. Experiments on the IEEE-CS datasets used in INEX show that, the query-oriented XML summary generated by our method is reasonable. © 2011 IEEE.

关键词： XML

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Selection of multimedia data source based on user feedback

Selection of multimedia data source based on user feedback

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2011 International Conference on Management of e-Commerce and e-Government, ICMeCG 2011

作者： Deng, Song Wan, Changxuan Liu, Xiping School of Information Technology Jiangxi University of Finance and Ecomomics Nanchang China School of Software Jiangxi Agricultural University Nanchang China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9780769545448

There are hundreds or thousands of web data sources providing data of relevance to a particular domain on the Web, so how to find a suitable set of sources quickly to integrate from a number of sources is becoming more and more important. Traditional data sources selection methods that are based on data quality do not consider quality characteristics of data sources under the different domains, but select the same quality dimensions for quality evaluation models. As a result, accuracies of a traditional method under different domains are quite different. In light of this, we propose a Web multimedia source selection method based on user feedback. We gain accurate core quality dimensions of data sources under the multimedia domain based on user feedback, and then achieve a quality estimation model of the multimedia data sources. The experiments on hundreds of real-world multimedia data sources have proved that our approach is efficient and accurate. © 2011 IEEE.

关键词： Accuracy Computers data Source data models databases Equations Mathematical model Multimedia Multimedia communication Quality Dimensions User Feedback Web data source data quality estimation model quality evaluation model quality multimedia computing mult

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In-memory join algorithms on GPUs for large-data 21

In-memory join algorithms on GPUs for large-data

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21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Guo, Chengxin Chen, Hong Key Lab of Data Engineering and Knowledge Engineering of Ministry of Education School of Information Renmin University of China Beijing China

ISBN: (纸本)9781728120584

In traditional databases, join is one of the most computationally expensive operations in query processing. During the past years, GPU has been adopted to improve the performance of join processing because of the features of massive parallelism and high memory bandwidth. Limited by the capacity of GPU memory and the absence of virtual memory management, however, handling the relations that exceed the capacity of the GPU memory is a challenge for GPU-based join algorithms. Because of the high computing throughput provided by GPUs and the low bandwidth of data communication between the CPUs and the GPUs, data have to be partitioned to fit the features of GPUs and to reduce the cost of data transmission. Furthermore, a series of novel techniques have been developed on the GPUs, which can benefit the join algorithms. In this work, we focus on the optimizing of processing join operator on large relations and propose the designs of in-memory hash join and sort-merge join on GPUs. We present the data partition method on the GPUs implemented with a pipeline mechanism. Furthermore, the shuffle instructions and the CUDA streams are applied in our algorithms to best utilize the GPUs. Experimental results indicate that our hash join algorithm delivers up to 1.51X and 1.24X speedup over the state-of-the-art hash join algorithm on CPUs on NVIDIA GTX1080ti-Pascal GPU and TitanV-Volta GPU respectively. For sort-merge join, our algorithm achieves up to 3.52X and 2.21X improvements on the same GPUs respectively compared to the baselines on CPUs. © 2019 IEEE.

关键词： Graphics processing unit

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