{"title":"An Unsupervised Approach for Constructing Word Similarity Network","authors":"Yu Hu, Tiezheng Nie, Derong Shen, Yue Kou","doi":"10.1109/WISA.2015.38","DOIUrl":"https://doi.org/10.1109/WISA.2015.38","url":null,"abstract":"To evaluate how much a pair of entities or documents are similar is a common problem for current applications. Most approaches for this problem are based on the co-occurrence. However, different terms or words may represent the same entity or similar semantic in the real world since a concept often has more than one way of expression. Existing works always focus on computing semantic relatedness of words. But relatedness cannot reflect the similarity most of the time, on the other hand, most of their corpus are from common data sources such as Wikipedia and are not useful for the specialized vocabulary. In this paper, we propose a novel unsupervised approach for evaluating the semantic similarity between words by mapping texts to vector space and computing prior information. In our approach, we construct a model that can identify the words representing the same entity in special context even though they don't belong to the same concept. At last, we construct a network of words in which paths between words can reflect the evolution process of concepts. Our experimental results show that that our approach gives an effective solution to discover the semantic relationship between words, especially for words in specialty domains.","PeriodicalId":198938,"journal":{"name":"2015 12th Web Information System and Application Conference (WISA)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125888037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design and Implementation of Streaming Application Execution Platform in Android","authors":"Binji Mo, Wenjuan Tang, Yang Xu, Guojun Wang","doi":"10.1109/WISA.2015.39","DOIUrl":"https://doi.org/10.1109/WISA.2015.39","url":null,"abstract":"Because of benefit from the strategy of open source and the strong ability of innovation, Android has become one of the most popular operating systems on mobile platform. While the explosive increase of mobile applications has leaded to several shortages in Android system, such as the limitations in hardware resources, complex and frequent updating of the applications. In this paper, we propose a new kind of mobile application model named Streaming Application Model by absorbing the concept of Transparent Computing. The applications are modularized into some independent components and stored on server. The android devices load and launch the components dynamically. Streaming Application Model can reduce the consumption of hardware resources and take away the complex and frequent application update processes for users, thus improving the user experience in Android devices.","PeriodicalId":198938,"journal":{"name":"2015 12th Web Information System and Application Conference (WISA)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126006319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Smart Task Scheduling Strategy of Orderly Power Utilization Based on Priority","authors":"Ji Tao, Z. Li, Wang Gang, Tan Yuan-Gang","doi":"10.1109/WISA.2015.64","DOIUrl":"https://doi.org/10.1109/WISA.2015.64","url":null,"abstract":"To the pressure caused by the improvement of the collection frequency in the course of high-frequency electrical load collection of orderly power utilization management platform, considering the existing channel carrying capacity, the number of concurrent tasks, collection frequency of tasks, the real-time performance of task execution and so on, this paper proposes a smart task scheduling strategy of orderly power utilization based on priority. Different task execution cycles setting for different priority tasks to make sure that high-priority tasks are timely implemented and the low-priority tasks are executed for the remainder of the execution cycle of high-priority tasks to take full advantage of channel resources and reduce the total task execution time. The actual application shows that the proposed strategy is efficient and feasible to achieve high-frequency real-time load collection and collection frequency is one minute while ensuring load collection tasks of common electric power users be performed.","PeriodicalId":198938,"journal":{"name":"2015 12th Web Information System and Application Conference (WISA)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123713930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chengcheng Su, Yaxin Yu, Mingfei Sui, Haijun Zhang
{"title":"Friend Recommendation Algorithm Based on User Activity and Social Trust in LBSNs","authors":"Chengcheng Su, Yaxin Yu, Mingfei Sui, Haijun Zhang","doi":"10.1109/WISA.2015.11","DOIUrl":"https://doi.org/10.1109/WISA.2015.11","url":null,"abstract":"In LBSNs (Location-based Social Networks), friend recommendation results are mainly decided by the number of common friends or depending on similar user preferences. However, lack of description of semantic information about user activity preferences, insufficiency in building social trust among user relationships and individual score ranking by a crowd or the person from third party of social networks make recommendation quality undesirable. Aiming at this issue, FRBTA algorithm is proposed in this paper to recommend best friends by considering multiple factors such as user semantic activity preferences, social trust. Experimental results show that the proposed algorithm is feasible and effective.","PeriodicalId":198938,"journal":{"name":"2015 12th Web Information System and Application Conference (WISA)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133357314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the Group Theory Based Model Transform Definition","authors":"Yanbing Jiang, Chunxiao Xing","doi":"10.1109/WISA.2015.12","DOIUrl":"https://doi.org/10.1109/WISA.2015.12","url":null,"abstract":"Although standards and tools of model transformation have gradually improved in recent years, a theoretical system about model transformation from the integrity perspective has not been put forward, which is important for building the model transformation process strategy and determining the feasibility and reversibility of a model transformation. This paper presents a model transform theory framework based on the group theory, which formally map model transform into a kind of Group that is made up with the abstract graphs and study the feasibility and reversibility of a model transformation on this base. Furthermore, the model transform process can be map into a recursive procedure of mathematical operation on subgroups, which can not only be a process strategy for model transformation but also provide a base for automatic generation method of model transformation.","PeriodicalId":198938,"journal":{"name":"2015 12th Web Information System and Application Conference (WISA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129630910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Hierarchical Clustering for Categorical Data Based on Holo-Entropy","authors":"Hao-jun Sun, Rongbo Chen, Shulin Jin, Yong Qin","doi":"10.1109/WISA.2015.18","DOIUrl":"https://doi.org/10.1109/WISA.2015.18","url":null,"abstract":"High dimensional data clustering is a difficult task in clustering analysis. Subspace clustering is an effective approach. The principle of subspace clustering is to maximize the retention of the original data information while searching for the minimal size of subspace for cluster representation. Based on information entropy and Holo-entropy, we propose an adaptive high dimensional weighted subspace clustering algorithm. The algorithm employs information entropy to extract the feature subspace, uses class compactness which binding Holo-entropy with weight in subspace for sub-clusters merging instead of the traditional similarity measurement method, and it selects the most compacted two sub-clusters to merge to achieve the maximum degree clustering effect. The algorithm is tested on nine UCI dataset, and compared with other algorithms. Our algorithm is better in both efficiency and accuracy than the other existing algorithms and has high reproducibility.","PeriodicalId":198938,"journal":{"name":"2015 12th Web Information System and Application Conference (WISA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133620027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhiqiang He, Zhongyi Wu, B. Zhou, Lei Xu, Weifeng Zhang
{"title":"Tourist Routs Recommendation Based on Latent Dirichlet Allocation Model","authors":"Zhiqiang He, Zhongyi Wu, B. Zhou, Lei Xu, Weifeng Zhang","doi":"10.1109/WISA.2015.66","DOIUrl":"https://doi.org/10.1109/WISA.2015.66","url":null,"abstract":"Tourism is an indispensable part of our life nowadays. At the same time, DIY tours become more and more popular. Traditionally, people have to spend a lot of time browsing websites and reading travel notes to select a suitable tourist route. With the help of tourist routes recommendation system, people can obtain their tourist routes satisfying their demands automatically. We improve a tourist routes recommendation system which based on Latent Dirichlet Allocation (LDA) model. The recommendation system firstly uses LDA model to dig out the hidden theme from a large number of documents. Then, by using Collaborative Filtering algorithm, grades are generated for each user to each travel routes. In this way, we can determine which route is most suitable to the user clearly. Our evaluation results indicate that our recommendation system is effective and has high level of satisfaction with user's hobbies and interests.","PeriodicalId":198938,"journal":{"name":"2015 12th Web Information System and Application Conference (WISA)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124681482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Blocked Rainbow Table Time-Memory Trade-Off Method","authors":"Hongwei Lu, Xiaoheng Zhu, Zaobin Gan","doi":"10.1109/WISA.2015.15","DOIUrl":"https://doi.org/10.1109/WISA.2015.15","url":null,"abstract":"The rainbow table algorithm has been widely applied to password recovery. However, it faces the issue of too much time or space consumption. Thus in this paper, a blocked rainbow table time-memory trade-off (BRT3) is proposed along with practical implementations. In the new method, the position of each starting point is stored instead of the starting point to reduce the storage consumption. Multiple rainbow blocks are used to reduce the merge probability of chains and improve the success rate of password cracking. A blocked memory structure is adopted to reduce the cryptanalysis time. We also analyze the existing time-memory trade-off methods and carry out comparison experiments to evaluate the performance. The experimental results show that the cryptanalysis time of the BRT3 method is no more than 2 minutes when cracking 200 MS-Windows LM password hashes on a general desktop machine with 2GB memory. What's more, the BRT3 method can also achieve up to a 50% reduction in the storage requirement and acquire an 11% increase in the success rate.","PeriodicalId":198938,"journal":{"name":"2015 12th Web Information System and Application Conference (WISA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125556317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Research on Column Concept Vector Based Web Table Matching","authors":"Chao Chen, Yue Zhao","doi":"10.1109/WISA.2015.61","DOIUrl":"https://doi.org/10.1109/WISA.2015.61","url":null,"abstract":"The Web consists of a huge number of structured data in the form of tables, which makes automatically integrating information from those tables of interest to ordinary users possible. A key problem of web table integration is the discovery of correspondences between web table columns. Most of traditional schema matching techniques can't work well because of the lack of schema information and the small number of instance in the web tables. This paper presents a method of web table matching which is based on column concept vector. Column Heading Matcher and Instance Matcher are employed to enhance the matching accuracy. A set of experiments are applied to real-world web tables and the results demonstrate that our method has higher precision and accuracy.","PeriodicalId":198938,"journal":{"name":"2015 12th Web Information System and Application Conference (WISA)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127156285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Efficient Name Lookup Scheme Based on Hash and Character Trie in Named Data Networking","authors":"Yunsong Tan, Shuhua Zhu","doi":"10.1109/WISA.2015.72","DOIUrl":"https://doi.org/10.1109/WISA.2015.72","url":null,"abstract":"Name lookup, as a key function of routers for forwarding and filtering packets in NDN, has confronted serious memory efficiency problem. To solve the problem, this paper presents an efficient NDN name lookup scheme -- Split Name character Trie(SNT). It first decomposed a name into components, which were then hashed to construct a trie. After that, the trie would be split into two smaller ones. When operating name lookup, a name would be split into two parts to conduct lookup on the two tries independently. Experimental results show that SNT supports longest prefix match very well. It can reduce 30% ~ 38% memory cost by component hash and can reduce 30% ~ 33% memory cost further by splitting trie. Despite of the extra memory cost of maintaining hash table, it still improves general memory efficiency by 23% ~ 49%.","PeriodicalId":198938,"journal":{"name":"2015 12th Web Information System and Application Conference (WISA)","volume":"57 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115485189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}