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The problem of predicting links or interactions between objects in a network, is an important task in network analysis. Along this line, link prediction between co-authors in a co-author network is a frequently studied problem. In most of these studies, authors are considered in a homogeneous network, \i.e., only one type of objects(author type) and one(More)
The problem of extracting structured data (<i>i.e</i>. lists, record sets, tables, etc.) from the Web has been traditionally approached by taking into account either the underlying markup structure of a Web page or the visual structure of the Web page. However, empirical results show that considering the HTML structure and visual cues of a Web page(More)
The availability of rich data from sources such as the World Wide Web, social media, and sensor streams is giving rise to a range of applications that rely on a clean, consistent, and integrated database built over these sources. Human input, or crowd-sourcing, is an effective tool to help produce such high-quality data. It is infeasible, however, to(More)
In this paper, we use the structural and relational information on the Web to find entity-pages. Specifically, given a Web site and an entity-page (e.g., department and faculty member homepage) we seek to find all of the entity-pages of the same type (e.g., all faculty members in the department). To do this, we propose a web structure mining method which(More)
The discovery and extraction of general lists on the Web continues to be an important problem facing theWeb mining community. There have been numerous studies that claim to automatically extract structured data (i.e. lists, record sets, tables, etc.) from the Web for various purposes. Our own recent experiences have shown that the list-finding methods used(More)
We consider the problem of automatically extracting general lists from the web. Existing approaches are mostly dependent upon either the underlying HTML markup or the visual structure of the Web page. We present HyLiEn an unsupervised, Hybrid approach for automatic List discovery and Extraction on the Web. It employs general assumptions about the visual(More)
Content based Image Retrieval (CBIR) is the problem of searching for digital images in large databases. It is the vital application of computer vision techniques to the image retrieval problem. One inherent problem associated with Content based Image Retrieval is the response time of the system to retrieve relevant result from the image database. The Apache(More)
Image retrieval and related operations are always a &apos;hotspot&apos; in the information era. Content-based image retrieval (CBIR) is a vastly developing area in the multimedia technology domain. To enhance security, we apply watermarking technique into the retrieval system and propose an approach for JEPG image retrieval. The proposed image retrieval(More)
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