Matches in ScholarlyData for { ?s ?p ?o. }
- 424 title "Structured Objects in OWL: Representation and Reasoning".
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- authorList hasFirstItem item-1.
- authorList hasItem item-1.
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- authorList hasItem item-3.
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- item-1 type ListItem.
- item-1 hasContent boris-motik.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent bernardo-cuenca-grau.
- item-2 next item-3.
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- item-3 type ListItem.
- item-3 hasContent ulrike-sattler.
- item-3 previous item-2.
- 431 creator lei-zhang-2.
- 431 creator zhiwei-li.
- 431 type InProceedings.
- 431 label "Improving Relevance Judgment of Web Search Results with Image Excerpts".
- 431 sameAs 431.
- 431 abstract "Current web search engines return result pages containing mostly text summary even though the matched web pages may contain informative pictures. A text excerpt (i.e. snippet) is generated by selecting keywords around the matched query terms for each returned page to provide context for user’s relevance judgment. However, in many scenarios, we found that the pictures in web pages, if selected properly, could be added into search result pages and provide richer contextual description because a picture is worth a thousand words. Such new summary is named as image excerpts. By well designed user study, we demonstrate image excerpts can help users make much quicker relevance judgment of search results for a wide range of query types. To implement this idea, we propose a practicable approach to automatically generate image excerpts in the result pages by considering the dominance of each picture in each web page and the relevance of the picture to the query. We also outline an efficient way to incorporate image excerpts in web search engines. Web search engines can adopt our approach by slightly modifying their index and inserting a few low cost operations in their workflow. Our experiments on a large web dataset indicate the performance of the proposed approach is very promising.".
- 431 hasAuthorList authorList.
- 431 hasTopic World_Wide_Web.
- 431 isPartOf proceedings.
- 431 keyword "Dominant Image".
- 431 keyword "Image Excerpts".
- 431 keyword "Usability".
- 431 keyword "User Interface".
- 431 keyword "Web Search".
- 431 title "Improving Relevance Judgment of Web Search Results with Image Excerpts".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
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- item-1 type ListItem.
- item-1 hasContent zhiwei-li.
- item-1 next item-2.
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- item-2 hasContent lei-zhang-2.
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- 45 creator abraham-bernstein.
- 45 creator andy-seaborne.
- 45 creator christoph-kiefer.
- 45 creator dave-reynolds.
- 45 creator markus-stocker.
- 45 type InProceedings.
- 45 label "SPARQL Basic Graph Pattern Optimization Using Selectivity Estimation".
- 45 sameAs 45.
- 45 abstract "In this paper, we formalize the problem of Basic Graph Pattern (BGP) optimization for SPARQL queries and main memory graph implementations of RDF data. We define and analyze the characteristics of heuristics for selectivity-based static BGP optimization. The heuristics range from simple triple pattern variable counting to more sophisticated selectivity estimation techniques. Customized summary statistics for RDF data enable the selectivity estimation of joined triple patterns and the development of efficient heuristics. Using the Lehigh University Benchmark (LUMB) we evaluate the performance of the heuristics for the queries provided by the LUBM and discuss some of them in more details.".
- 45 hasAuthorList authorList.
- 45 hasTopic World_Wide_Web.
- 45 isPartOf proceedings.
- 45 keyword "Basic Graph Pattern Optimization".
- 45 keyword "Query Optimization".
- 45 keyword "SPARQL".
- 45 keyword "Semantic Web".
- 45 title "SPARQL Basic Graph Pattern Optimization Using Selectivity Estimation".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
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- authorList hasItem item-3.
- authorList hasItem item-4.
- authorList hasItem item-5.
- authorList hasLastItem item-5.
- item-1 type ListItem.
- item-1 hasContent markus-stocker.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent andy-seaborne.
- item-2 next item-3.
- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent abraham-bernstein.
- item-3 next item-4.
- item-3 previous item-2.
- item-4 type ListItem.
- item-4 hasContent christoph-kiefer.
- item-4 next item-5.
- item-4 previous item-3.
- item-5 type ListItem.
- item-5 hasContent dave-reynolds.
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- 454 creator jiang-ming-yang.
- 454 creator lei-zhang-2.
- 454 creator rui-cai.
- 454 creator wei-lai.
- 454 creator yida-wang.
- 454 type InProceedings.
- 454 label "iRobot: An Intelligent Crawler for Web Forums".
- 454 sameAs 454.
- 454 abstract "We study in this paper the Web forum crawling problem, which is a very fundamental step in many Web applications, such as search engine and Web data mining. As a typical user-created content (UCC), Web forum has become an important resource on the Web due to its rich information contributed by millions of Internet users every day. However, Web forum crawling is not a trivial problem due to the in-depth link structures, the large amount of duplicate pages, as well as many invalid pages caused by login failure issues. In this paper, we propose and build a prototype of an intelligent forum crawler, iRobot, which has intelligence to understand the content and the structure of a forum site, and then decide how to choose crawling routings among different kinds of pages. To do this, we first randomly sample (download) a few pages from the target forum site, and introduce the page content layout as the characteristics to group those pre-sampled pages and recover the forum's sitemap. After that, we select an optimal routing path which only traverses informative pages and skips invalid and duplicate ones. The extensive experimental results on several forums show the performance of our system in the following aspects: 1) Effectiveness – Compared to a generic crawler, iRobot significantly decreases the duplicate and invalid pages; 2) Efficiency – With a small cost of pre-sampling a few pages for learning the necessary knowledge, iRobot saves substantial network bandwidth and storage as it only fetches informative pages from a forum site; and 3) Long threads that are divided into multiple pages can be re-concatenated and archived as a whole thread, which is of great help for further indexing and data mining.".
- 454 hasAuthorList authorList.
- 454 hasTopic World_Wide_Web.
- 454 isPartOf proceedings.
- 454 keyword "Forum crawler".
- 454 keyword "repetitive pattern".