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- item-3 hasContent hyunsun-kim.
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- 9 creator davy-van-deursen.
- 9 creator joaquim-gabarro.
- 9 creator rik-van-de-walle.
- 9 creator ruben-verborgh.
- 9 creator sam-coppens.
- 9 creator thomas-steiner.
- 9 type InProceedings.
- 9 label "Functional Descriptions as the Bridge between Hypermedia APIs and the Semantic Web".
- 9 sameAs 9.
- 9 abstract "The early visions for the Semantic Web, from the infamous 2001 Scientific American article by Berners-Lee et al., feature intelligent agents that can autonomously perform tasks like discovering information, scheduling events, finding execution plans for complex operations, and in general, use reasoning techniques to come up with sense-making and traceable decisions. While today – more than ten years later – the building blocks (1) resource-oriented rest infrastructure, (2) Web apis, and (3) Linked Data are in place, the envisioned intelligent agents have not landed yet. In this paper, we explain why capturing functionality is the connection between these three building blocks, and introduce the functional api description format RESTdesc that creates this bridge between rest apis and the Semantic Web. Rather than adding yet another component to the Semantic Web stack, RESTdesc offers instead concise descriptions that reuse existing vocabularies to guide hypermedia-driven agents. Its versatile capabilities are illustrated by a real-life agent use case for Web browsers wherein we demonstrate that RESTdesc functional descriptions are capable of fulfilling the promise of autonomous agents on the Web.".
- 9 hasAuthorList authorList.
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- 9 keyword "API descriptions".
- 9 keyword "REST".
- 9 keyword "Semantic Web".
- 9 keyword "Service descriptions".
- 9 keyword "Web APIs".
- 9 keyword "Web services".
- 9 keyword "hypermedia".
- 9 title "Functional Descriptions as the Bridge between Hypermedia APIs and the Semantic Web".
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- 100 creator bingjun-sun.
- 100 creator c-lee-giles.
- 100 creator prasenjit-mitra.
- 100 creator qingzhao-tan.
- 100 type InProceedings.
- 100 label "Extraction and Search of Chemical Formulae in Text Documents on the Web".
- 100 sameAs 100.
- 100 abstract "Often scientists seek to search for articles on the Web related to a particular chemical. When a scientist searches for a chemical formula using a search engine today, she gets back articles where the exact keyword string expressing the chemical formula is found. Searching for the exact occurrence of keywords while searching results in two problems for this domain: a) if the author searches for CH4 and the article has H4C, the article is not returned, and b) ambiguous searches like "He" return all documents where Helium is mentioned as well as documents where the pronoun "he" occurs. To remedy these deficiencies, we propose a chemical formula search engine. To build a chemical formula search engine, we must solve the following problems: (1) extract chemical formulae from text documents, (2) index chemical formulae, and (3) design a ranking function for articles where the chemical formulae occur. Furthermore, query models are introduced for formula search, and for each a scoring scheme based on features of partial formulae is proposed to measure the relevance of chemical formulae and queries. We evaluate algorithms for identifying chemical formulae in documents using a classification method based on Support Vector Machines (SVM), and a probabilistic model based on conditional random fields (CRF). Different methods for SVM and CRF to tune the trade-off between recall and precision for imbalanced data are proposed to improve the over-all performance. A feature selection method based on frequency and discrimination is used to remove uninformative and redundant features. Experiments show that our approaches of chemical formula extraction work well, especially after trade-off tuning. The results also demonstrate that feature selection can reduce the index size without changing the ranked query results much.".
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- 100 title "Extraction and Search of Chemical Formulae in Text Documents on the Web".
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- item-1 hasContent bingjun-sun.
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- 111 creator hao-chen.
- 111 creator ming-ma.
- 111 creator yi-min-wang.
- 111 creator yuan-niu.
- 111 type InProceedings.
- 111 label "Spam Double-Funnel: Connecting Web Spammers with Advertisers".
- 111 sameAs 111.
- 111 abstract "Spammers use questionable search engine optimization (SEO) techniques to promote their spam links into top search results. In this paper, we focus on one prevalent SEO technique, redirection, where one can identify spam pages by the third-party domains that these pages redirect traffic to. We propose a five-layer, double-funnel model for describing end-to-end redirection spam, and identify prominent domains on each layer using two sets of commercial keywords ' one targeting spammers and the other targeting advertisers. The methodology and findings are useful for search engines to strengthen their ranking algorithms against spam, for legitimate website owners to locate and remove spam doorway pages, and for legitimate advertisers to identify unscrupulous syndicators who serve ads on spam pages.".