The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Pairwise link discovery approaches for the Web of Data do not scale to many sources thereby limiting the potential for data integration. We thus propose a holistic approach for linking many data sources based on a clustering of entities representing the same real-world object. Our clustering approach utilizes existing links and can deal with entities of different semantic types. The approach is able...
A RDF graph is typically stored in XML file or relational database. However, when it becomes a large RDF graph, an alternative way to handle the storing and query RDF graph or linked data is to use MapReduce algorithm and Hadoop framework. In this paper, we propose a supporting tool to perform data transfer and query on big RDF graph. We intend to reduce the access time and query response time by...
Data provenance is currently a hot issue, and many webpages still lack provenance annotation. PROV-O is an emerging W3C recommendation for a provenance data model and language. In this paper, through the analysis of web document derivation, we define a document as an entity and extract a number of semantic properties about document features. A semantic similarity clustering method is used to determine...
This paper proposes a new method to cluster law texts based on referential relation of laws. We extract law entities (an entity represents a law) and their referential relation from law texts. Then SimRank algorithm is applied to calculate law entity's similarity through referential relation and law clustering is carried out based on the SimRank similarity. This is the first time to apply SimRank...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.