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Web search results

Xem 1-20 trên 41 kết quả Web search results
  • Is it possible to use sense inventories to improve Web search results diversity for one word queries? To answer this question, we focus on two broad-coverage lexical resources of a different nature: WordNet, as a de-facto standard used in Word Sense Disambiguation experiments; and Wikipedia, as a large coverage, updated encyclopaedic resource which may have a better coverage of relevant senses in Web pages.

    pdf10p hongdo_1 12-04-2013 32 1   Download

  • This paper proposes to solve the bottleneck of finding training data for word sense disambiguation (WSD) in the domain of web queries, where a complete set of ambiguous word senses are unknown. In this paper, we present a combination of active learning and semi-supervised learning method to treat the case when positive examples, which have an expected word sense in web search result, are only given. The novelty of our approach is to use “pseudo negative examples” with reliable confidence score estimated by a classifier trained with positive and unlabeled examples.

    pdf4p hongphan_1 15-04-2013 47 2   Download

  • Web search engines today typically show results as a list of titles and short snippets that summarize how the retrieved documents are related to the query. However, recent research suggests that longer summaries can be preferable for certain types of queries. This paper presents empirical evidence that judges can predict appropriate search result summary lengths, and that perceptions of search result quality can be affected by varying these result lengths. These findings have important implications for search results presentation, especially for natural language queries. ...

    pdf9p hongphan_1 15-04-2013 36 2   Download

  • Google serves some 80 percent of all search queries on the Internet, making it by far the most popular search engine. Its popularity is due not only to excellent search effectiveness, but also extensive querying capabilities. However, we should also remember that the Internet is a highly dynamic medium, so the results presented by Google are not always up-to-date – some search results might be stale, while other relevant resources might not yet have been visited by Googlebot (the automatic script that browses and indexes Web resources for Google)....

    pdf12p thuylinh 07-09-2009 1619 8   Download

  • Web text has been successfully used as training data for many NLP applications. While most previous work accesses web text through search engine hit counts, we created a Web Corpus by downloading web pages to create a topic-diverse collection of 10 billion words of English. We show that for context-sensitive spelling correction the Web Corpus results are better than using a search engine. For thesaurus extraction, it achieved similar overall results to a corpus of newspaper text.

    pdf8p bunthai_1 06-05-2013 37 3   Download

  • We use search engine results to address a particularly difficult cross-domain language processing task, the adaptation of named entity recognition (NER) from news text to web queries. The key novelty of the method is that we submit a token with context to a search engine and use similar contexts in the search results as additional information for correctly classifying the token. We achieve strong gains in NER performance on news, in-domain and out-of-domain, and on web queries.

    pdf11p hongdo_1 12-04-2013 30 2   Download

  • Searching for a person name in a Web Search Engine usually leads to a number of web pages that refer to several people sharing the same name. In this paper we study whether it is reasonable to assume that pages about the desired person can be filtered by the user by adding query terms. Our results indicate that, although in most occasions there is a query refinement that gives all and only those pages related to an individual, it is unlikely that the user is able to find this expression a priori. ...

    pdf4p hongphan_1 15-04-2013 35 1   Download

  • Fast, focused instruction for beginning Web developers W3Schools.com is the number one online education source for beginning Web developers. This attractive two-color book contains concise, highly focused tutorials in the proven W3Schools instructional format, with an easy-to-use reference of JavaScript Objects and the HTML DOM included. Novice developers will quickly learn to create interactive Web pages using the most popular Web scripting language.

    pdf267p ngochieu123 29-05-2012 226 101   Download

  • Google, the most popular search engine worldwide, provides web surfers with an easy-to-use guide to the Internet, with web and image searches, language translation, and a range of features that make web navigation simple enough for even the novice user. What many users don't realize is that the deceptively simple components that make Google so easy to use are the same features that generously unlock security flaws for the malicious hacker.

    pdf529p m3onh0x84 10-04-2011 258 84   Download

  • The web page is derived from data that changes frequently, results from search engines and order confirmation pages at on-line stores, The web page uses information from databases or other server-side sources.For a general Servlet you must subclass javax.servlet.GenericServlet...

    pdf68p hoangdoanisuit 10-09-2011 84 24   Download

  • This module introduces students to planning a search strategy, conducting searches, and creating and editing indexes for searching. After completing this module, students will be able to: Discuss the three search options in Microsoft® SharePoint™ Portal Server 2001, use the two Search Web Parts to perform simple and advanced searches, and apply various techniques for maximizing search results.

    pdf44p vuthuong 11-08-2009 81 15   Download

  • Adhere to character limits Title tags are critical because search engines not only use them when deciding what a web page is about, but they also appear in search results as the first line “Title” of your listing. Think of title tags more as a "Title Keyword Tag" and include keywords that users would likely search for to find the content on that page. Keep them short and sweet. They are the first thing people searching for your site will see, and can never be more than Google’s limit of 69 characters, including spaces. ...

    pdf1p kienk6e 01-04-2011 54 6   Download

  • hing for. For instance, despite Vietnam’s growing allure as a vacation destination, visitors to sites Bonanza or botnet? Next time you search for a celebrity photo or “how to” hint, pay special attention to the top-level domains (TLDs), the last few characters at the end of the URL in the search results. In this year’s Mapping the Mal Web study, McAfee found that web risk climbed to a record 6.2% of more than 27 million live domains we evaluated for this report. If users don’t click with care, simply viewing a page can return much more than they bargained for.

    pdf27p doiroimavanchuadc 06-02-2013 38 4   Download

  • Any organization that has a searchable web site or intranet is sitting on top of hugely valuable and usually under-exploited data: logs that capture what users are searching for, how often each query was searched, and how many results each query retrieved. Search queries are gold: they are real data that show us exactly what users are searching for in their own words. This book shows you how to use search analytics to carry on a conversation with your customers: listen to and understand their needs, and improve your content, navigation and search performance to meet those needs....

    pdf372p rose_12 06-12-2012 34 3   Download

  • This paper describes Read-X, a system designed to identify text that is appropriate for the reader given his thematic choices and the reading ability associated with his educational background. To our knowledge, Read-X is the first web-based system that performs real-time searches and returns results classified thematically and by reading level within seconds.

    pdf4p bunthai_1 06-05-2013 62 3   Download

  • The PageRank algorithm, used in the Google search engine, greatly improves the results of Web search by applying probabilistic model on the link structure of Webs to evaluate the “importance” of Webs. In PageRank probabilistic model, the links and webs are uniform, so the rank score of webs are quite independent from their content. In practice, the researchers often hope that the web results can be ranked by their proposed topics. Moreover, when computer’s techniques solve given problems ineffectively, it’s necessary to do better research in theoretical problems. ...

    pdf12p tuanlocmuido 19-12-2012 29 2   Download

  • We query Web Image search engines with words (e.g., spring) but need images that correspond to particular senses of the word (e.g., flexible coil). Querying with polysemous words often yields unsatisfactory results from engines such as Google Images. We build an image search engine, I DIOM, which improves the quality of returned images by focusing search on the desired sense. Our algorithm, instead of searching for the original query, searches for multiple, automatically chosen translations of the sense in several languages. ...

    pdf4p hongphan_1 15-04-2013 26 1   Download

  • This paper presents an application of PageRank, a random-walk model originally devised for ranking Web search results, to ranking WordNet synsets in terms of how strongly they possess a given semantic property. The semantic properties we use for exemplifying the approach are positivity and negativity, two properties of central importance in sentiment analysis.

    pdf8p hongvang_1 16-04-2013 44 1   Download

  • This paper proposes a method of collecting a dozen terms that are closely related to a given seed term. The proposed method consists of three steps. The first step, compiling corpus step, collects texts that contain the given seed term by using search engines. The second step, automatic term recognition, extracts important terms from the corpus by using Nakagawa’s method. These extracted terms become the candidates for the final step. The final step, filtering step, removes inappropriate terms from the candidates based on search engine hits.

    pdf4p bunbo_1 17-04-2013 30 1   Download

  • After studying this chapter you will be able to understand: What is SEO? What are organic results? Why SEO? How does a search engine works? conceptual categories, SEO tactics and methods, mobile SEO, what is mobile SEO, techniques of mobile SEO, tools for mobile SEO.

    ppt51p tieu_vu20 24-09-2018 19 0   Download

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