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- item-2 hasContent sergio-di-martino.
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- 339 creator fabien-de-montgolfier.
- 339 creator toufik-bennouas.
- 339 type InProceedings.
- 339 label "Random Web Crawls".
- 339 sameAs 339.
- 339 abstract "This paper proposes a random Web crawl model. A Web crawl is a (biased and partial) image of the Web. This paper deals with the hyperlink structure, i.e. a Web crawl is a graph, whose vertices are the pages and whose edges are the hypertextual links. Of course a Web crawl has a very particular structure; we recall some known results about it. We then propose a model generating similar structures. Our model simply simulates a crawling, i.e. builds and crawls the graph at the same time. The graphs generated have lot of known properties of Web crawls. Our model is simpler than most random Web graph models, but captures the sames properties. Notice that it modelizes the crawling process instead of the page writting process of Web graph models.".
- 339 hasAuthorList authorList.
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- 339 title "Random Web Crawls".
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- 342 creator ramakrishnan-srikant.
- 342 creator roberto-bayardo.
- 342 creator yiming-ma.
- 342 type InProceedings.
- 342 label "Scaling Up All-Pairs Similarity Search".
- 342 sameAs 342.
- 342 abstract "Given a large collection of sparse vector data in a high dimensional space, we investigate the problem of finding all pairs of vectors whose similarity score (as determined by a function such as cosine distance) is above a given threshold. We propose novel optimization and indexing techniques for this problem, resulting in an algorithm that is both faster and simpler than the previous state-of-the-art approaches. We demonstrate the effectiveness of our algorithm on the public DBLP dataset, and on two real-world web applications: generating recommendations for the Orkut social network, and computing pairs of similar queries from search snippet data among the 5 million most frequently issued Google queries. Our algorithm is between 5 times to 20 times faster than previous algorithms on these datasets.".
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- 342 title "Scaling Up All-Pairs Similarity Search".
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- item-1 hasContent roberto-bayardo.
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- item-3 hasContent ramakrishnan-srikant.
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- 366 creator bhaskaran-raman.
- 366 creator sayandeep-sen.
- 366 type InProceedings.
- 366 label "Long Distance Wireless Mesh Network Planning: Problem Formulation and Solution".
- 366 sameAs 366.
- 366 abstract "Several research efforts as well as deployments have chosen IEEE 802.11 as a low-cost, long-distance access technology to bridge the digital divide. In this paper, we consider the important issue of planning such networks to the minimize system cost. This is a non-trivial task since it involves several sets of variables: the network topology, tower heights, antenna types to be used and their orientations, and radio transmit powers. The task is further complicated due to the presence of network performance constraints, and the inter-dependence among the variables. Our first contribution in this paper is the formulation of this problem in terms of the variables, constraints and the optimization criterion. Our second contribution is in identifying the dependencies among the variables and breaking-down the problem into four tractable sub-parts. In this process, we extensively use domain knowledge to strike a balance between tractability and practicality.<br /><br /> We have evaluated the proposed algorithms using random input sets as well as real-life instances with success. We have been able to show detailed planning of network topology, required tower heights, antenna types, and transmit powers for the Ashwini project, a long distance WiFi network under deployment in Andhra Pradesh, India, In this case, we are able to achieve within 2\% additional cost of a lower bound estimate.".
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- 366 title "Long Distance Wireless Mesh Network Planning: Problem Formulation and Solution".
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- item-1 hasContent sayandeep-sen.
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- 391 creator fabian-m-suchanek.
- 391 creator gerhard-weikum.
- 391 creator gjergji-kasneci.
- 391 type InProceedings.
- 391 label "Yago: A Core of Semantic Knowledge - Unifying WordNet and Wikipedia".
- 391 sameAs 391.
- 391 abstract "We present YAGO, a light-weight and extensible ontology with high coverage and quality. YAGO builds on entities and relations and currently contains roughly 900,000 entities and 5,000,000 facts. This includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as hasWonPrize). The facts have been automatically extracted from the unification of Wikipedia and WordNet, using a carefully designed combination of rule-based and heuristic methods described in this paper. The resulting knowledge base is a major step beyond WordNet: in quality by adding knowledge about individuals like persons, organizations, products, etc. with their semantic relationships -- and in quantity by increasing the number of facts by more than an order of magnitude. Our empirical evaluation of fact correctness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable, extensible, and compatible with RDFS. Finally, we show how YAGO can be further extended by state-of-the-art information extraction techniques.".
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- 391 title "Yago: A Core of Semantic Knowledge - Unifying WordNet and Wikipedia".
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- item-1 hasContent fabian-m-suchanek.
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