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Recently, keyword search on XML data has received much attention. Existing XML keyword search algorithms are all based on Dewey labeling, and this method in the calculation of the common ancestor would suffer from the CAR (common-ancestor-repetition) problem. In this paper, we propose a novel index based on interval encoding, namely IS-Index. We then design an efficient algorithm based on this structure,...
The Data on the Web Best Practices Working Group, as part of W3C Data Activity, is standardizing the Data Quality Vocabulary (DQV) for expressing data quality of datasets published on the Web. By exploiting such DQV-based quality metadata associated to the datasets in a data portal, data consumers can achieve data quality-based filtering and ranking of datasets on the portal's conventional search...
With the growing scale of the Internet, the amount of data is increasing rapidly as well. In order to improve the user experience, the recommendation system came into being. It recommends products to the user by analyzing the user's behavior. In the recommendation system, collaborative filtering algorithm is one of the most widely used algorithms. While the traditional collaborative filtering is no...
Traditional recommendation only uses the single model of selection or rating to mining the users' interests. Network-Based Inference (NBI) is typical of selection single model. In order to make full use of information, in this paper, Recommendation based on bipartite network of two-step model(RBNTM) is put forward. The method on the basis of Network-based inference, considering scores also reflects...
Recently, subgraph matching has been implemented in more and more domains, such as social network and semantic web. An approximated solution for subgraph matching named strong simulation has been put forward. Strong Simulation can preserve the topology of data graphs and find a bounded number of matches, but the complexity further holds a cubic-time, so it's yet intractable to deal with large graphs...
In recent years, data fusion has been applied to many different application areas such as neural networks, classification, multi-sensor systems, image processing, information retrieval, Web search among others. Linear combination is a popular data fusion method due to its flexibility. Proper weight assignment is a key issue for its success. In this paper, we apply the differential evolution optimization...
Most of the existing cloud service strategies are scheduling algorithm based on user's satisfaction or QoS. The former does not consider physical resource utilization, while the latter ignores the satisfaction of the user's experience. This paper proposes a multi-objective cloud service model, which is based on the user's dynamic demand and resource utilization. In addition, it designs a multi-objective...
With the growing amount of information available online, context-aware recommender systems have emerged to improve the precision of recommendation. Matrix factorization models are the state-of-the-art in these systems, especially for multi-context recommendation. However, existing models ignored either context influence or entity sensitivity. That is, they assume that one entity (user or item) shares...
According to the characteristics of Weibo event, this paper analyzes the advantages and disadvantages of the traditional K-means algorithm, and proposes the K-means clustering algorithm of events based on variable time granularity. The experiments show that the improved algorithm is more suitable for clustering analysis of Weibo event, improves the efficiency of clustering algorithm, and solves the...
Transaction price accurate recommendation is a hot issue for buyer and seller on bidding information services in Chinese electricity market, a novel multilayer collaborative filtering algorithm is proposed to solve the bidding prices accurate mining problem. A three-tier relationship model of user-item-attribute is described to accommodate the real electricity transaction on bidding price service...
With the development of the Web2.0, micro-blogs gradually become a common essential part of the public life. The reviews in the micro-blogs have huge hidden value. Many machine learning approaches have been used to solve sentiment analysis. However, the features used in existing researches are still not enough. To improve the accuracy of sentiment analysis, in this paper, we use a classification approach...
With the rapid development of database and web technology, the way data organized and presented is becoming increasingly complicated while data sources are also intermingled with inaccurate information. Therefore, studies in truth discovery becomes overwhelmingly significant for it is critical for netizens to identify sources of high quality as well as to select the most accurate information from...
Quality-of-Service (QoS) is widely employed for describing non-functional characteristics of Web services. QoS prediction for Web services is a hot research problem in service computing. Collaborative Filtering (CF) has been widely used as a prediction technique. However, CF may suffer from data scarcity problem, which causes unreliable prediction. In this paper, we propose a novel location-based...
Although many different community detection algorithms have been proposed to detect community structures in complex networks, how to effectively detect community structures is still a great challenge. Seed-centric methods is one of the most effective solutions for community detection. To more, in this paper, we propose a novel density-based seed expansion algorithm, namely, DenSeC, which can easily...
Service has become the basic way to access and enlarge the capability of all kinds of infrastructure. But now, service-based software system based on SOA lacks of runtime iterative re-aggregation process management and exception handling. And current approaches can't align services aggregation with requirements to overcome the runtime exceptions and deal with services resource insufficiency and context...
Incidents of public security have an ascendant trend in recent years all over the world, and it is more important to understand the correlation of different kinds of public security incidents. With the popularization of the Internet, numerous web messages can provide resources to do that. However, an important challenge is that the web messages are often heterogeneous and unstructured. In this paper,...
In order to improve the retrieval performance in the educational resource database, this paper designs an retrieval mechanism called ERRM based on Lucene and topic index. Firstly, this paper introduces the full-text search engine – Lucene, and studies in depth its internal implementation. Then by the way of the topic index which is learned by the topic model, this paper researches how to successfully...
With the rapid growth of the number of short text, how to effectively realize the automatic classification of short text is needed to be solved in the information domain. According to the characteristics of short text, this paper proposes Bagging_NB & Bagging_BSJ, which are two classification algorithms based on the improvement of current integrated classifiers. Traditional classifier NB, SVM,...
Traveling companions are object groups that move together in a period of time. To quickly identify traveling companions from a special kind of streaming traffic data, called Automatic Number Plate Recognition (ANPR) data, this paper proposes a framework and several algorithms to discover companion vehicles. Compared to related approaches, our main contribution is that the framework can instantly detect...
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