Se Wang

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Se Wang is an author.


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Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Happy or not: Generating topic-based emotional heatmaps for culturomics using CyberGIS CyberGIS
Digital HASS
Sentiment mining
Spatial text mining
2012 IEEE 8th International Conference on E-Science, e-Science 2012 English 2012 The field of Culturomics exploits "big data" to explore human society at population scale. Culturomics increasingly needs to consider geographic contexts and, thus, this research develops a geospatial visual analytical approach that transforms vast amounts of textual data into emotional heatmaps with fine-grained spatial resolution. Fulltext geocoding and sentiment mining extract locations and latent "tone" from text-based data, which are combined with spatial analysis methods - kernel density estimation and spatial interpolation - to generate heatmaps that capture the interplay of location, topic, and tone toward narrative impacts. To demonstrate the effectiveness of the approach, the complete English edition of Wikipedia is processed using a supercomputer to extract all locations and tone associated with the year of 2003. An emotional heatmap ofWikipedia's discussion of "armed conflict" for that year is created using the spatial analysis methods. Unlike previous research, our approach is designed for exploratory spatial analysis of topics in text archives by incorporating multiple attributes including the prominence of each location mentioned in the text, the density of a topic at each location compared to other topics, and the tone of the topics of interest into a single analysis. The generation of such fine-grained emotional heatmaps is computationally intensive particularly when accounting for the multiple attributes at fine scales. Therefore a CyberGIS platform based on national cyberinfrastructure in the United States is used to enable the computationally intensive visual analytics. 0 0
Survey on statics of Wikipedia Collective intelligence
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University Chinese 2012 This paper mainly focuses on the Wikipedia, a collaborative editing pattern in Web 2. 0. The articles, editors and the editing relationships between the two ones are three important components in Wikipedia statistical analysis. We collected different kinds of statistical tools, methods and results, and further analyzed the problems in the current statistics researches and discussed the possible resolutions. 0 0
Quality Evaluation of Wikipedia Articles through Edit History and Editor Groups Web Technologies and Applications English 2011 Wikipedia is well known as a free encyclopedia, which is a type of collaborative repository system that allows the viewer to create and edit articles directly in the web browser. The weakness of the Wikipedia system is the possibility of manipulation and vandalism cannot be ruled out, so that the quality of any given Wikipedia article is not guaranteed. It is an important work to establish a quality evaluation method to help users decide how much they should trust an article in Wikipedia. In this paper we investigate the edit history of Wikipedia articles and propose a model of network structure of editors. We propose an algorithm to calculate the network structural indicator restoreratio. We use the proposed indicator combined with existing metrics to predict the quality of Wikipedia articles through support vector machine technology. The experimental results show that the proposed indicator has better performance in quality evaluation than several existing metrics. 0 0
Quality evaluation of wikipedia articles through edit history and editor groups Edit network
Quality evaluation
Web mining
Web trust
APWeb English 2011 0 0
Quality of articles in Wikipedia Collective intelligence
Quality of article evaluation
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University Chinese 2011 The recent research of wikipediais is firs briefly analyzed, especially on the statistics of quality of articles in Wikipedia. Then the automatic evaluating methods of article quality are discussed. The methods mainly include two kinds: the correlation-based analysis and cooperation modeling. Furthermore, we present the open problems of automatic quality evaluation and the possiblepromotions of collective intelligence. 0 0
Dynamic topic detection and tracking based on knowledge base Knowledge base
Topic detection
Topic tracking
Topic update
Proceedings - 2010 3rd IEEE International Conference on Broadband Network and Multimedia Technology, IC-BNMT2010 English 2010 In order to solve the sparse initial information problem when the topic model was established ever before, this paper establishes the Wikipedia based news event knowledge base. Referring to this knowledge base, we calculate the weight of the news model, make the similarity measurement based on the time distance, make the clustering based on time line, and apply the dynamic threshold strategy to detect and track the topics automatically in the news materials. The experiment result verifies the validity of this method. 0 0
Exploiting semantic tags in XML retrieval Lecture Notes in Computer Science English 2010 With the new semantically annotated Wikipedia XML corpus, we attempt to investigate the following two research questions. Do the structural constraints in CAS queries help in retrieving an XML document collection containing semantically rich tags? How to exploit the semantic tag information to improve the CO queries as most users prefer to express the simplest forms of queries? In this paper, we describe and analyze the work done on comparing CO and CAS queries over the document collection at INEX 2009 ad hoc track, and we propose a method to improve the effectiveness of CO queries by enriching the element content representations with semantic tags. Our results show that the approaches of enriching XML element representations with semantic tags are effective in improving the early precision, while on average precisions, strict interpretation of CAS queries are generally superior. 0 0