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(P2P) computing model has fueled the autonomous data sharing over the Internet in a more flexible fashion. Needless to say, XML data retrieval in P2P systems has become attractive to professionals in both research and industrial communities. In this paper, we propose a Bloom-Filter based keyword search framework for XML
Recent research has shown that keyword search is a friendly and potentially effective way to retrieve information of interest over relational databases. Existing work has generally focused on implementing keyword search in centralized databases. This paper addresses keyword search over distributed databases. We adopts
Social applications associate a set of user defined keywords named tags when publishing social objects in order to locate them later. We propose T-DHT, a hybrid unstructured-structured DHT based approach, to cope with the high demanding requirements of social applications, in a fully scalable, distributed and balanced
overall semantic concepts. However, in the literature, most researches were conducted within only one single domain. In this paper we propose an unsupervised technique that builds context-independent keyword lists for desired visual concept modeling using WordNet. Furthermore, we propose an extended speech-based visual
We present a simple yet novel technique for prefix search in P2P networks. The idea is to extract characters and their position information in a keyword to index objects. Our index scheme can achieve quite balanced loads, avoid hop-spots and single point of failure, reduce storage and maintenance costs, and offer some
photographs show that our approach gives better results in terms of recall and precision measures than state-of-the-art frameworks loosely coupling keyword-based query modules and relevance feedback processes operating on low-level features
the page weight based on incoming and outgoing hyperlinks in the page. The author input takes into account the weight of relevance in terms of keywords or phrases of a page specified by the page creators. Our evaluation shows that the proposed search method performs better than that using only the page ranking algorithm
Environment), a 3D interface for World-Wide Web information visualization and browsing. It uses the mathematical theory of concept analysis to conceptually cluster objects. So-called conceptual scales for attributes, such as location, title, keywords, topic, size, or modification time, provide a formal mechanism that
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.