Search (27 results, page 1 of 2)

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Abstract

This paper is about search of photos in photo databases of agencies which sell photos over the Internet. The problem is far from the behavior of photo databases managed by librarians and also far from the corpora generally used for research purposes. The descriptions use mainly single words and it is well known that it is not the best way to have a good search. This increases the problem of semantic ambiguity. This problem of semantic ambiguity is crucial for cross-language querying. On the other hand, users are not aware of documentation techniques and use generally very simple queries but want to get precise answers. This paper gives the experience gained in a 3 year use (2006-2008) of a cross-language access to several of the main international commercial photo databases. The languages used were French, English, and German.

Date

17. 4.2012 14:25:22

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Abstract

The explosion of the information available on the Internet has made traditional information retrieval systems, characterized by one size fits all approaches, less effective. Indeed, users are overwhelmed by the information delivered by such systems in response to their queries, particularly when the latter are ambiguous. In order to tackle this problem, the state-of-the-art reveals that there is a growing interest towards contextual information retrieval (CIR) which relies on various sources of evidence issued from the user's search background and environment, in order to improve the retrieval accuracy. This chapter focuses on mobile context, highlights challenges they present for IR, and gives an overview of CIR approaches applied in this environment. Then, the authors present an approach to personalize search results for mobile users by exploiting both cognitive and spatio-temporal contexts. The experimental evaluation undertaken in front of Yahoo search shows that the approach improves the quality of top search result lists and enhances search result precision.

Date

20. 4.2012 13:19:22

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Abstract

Few companies in history have ever been as successful and as admired as Google, the company that has transformed the Internet and become an indispensable part of our lives. How has Google done it? Veteran technology reporter Steven Levy was granted unprecedented access to the company, and in this revelatory book he takes readers inside Google headquarters-the Googleplex-to show how Google works. While they were still students at Stanford, Google cofounders Larry Page and Sergey Brin revolutionized Internet search. They followed this brilliant innovation with another, as two of Google's earliest employees found a way to do what no one else had: make billions of dollars from Internet advertising. With this cash cow (until Google's IPO nobody other than Google management had any idea how lucrative the company's ad business was), Google was able to expand dramatically and take on other transformative projects: more efficient data centers, open-source cell phones, free Internet video (YouTube), cloud computing, digitizing books, and much more. The key to Google's success in all these businesses, Levy reveals, is its engineering mind-set and adoption of such Internet values as speed, openness, experimentation, and risk taking. After its unapologetically elitist approach to hiring, Google pampers its engineers-free food and dry cleaning, on-site doctors and masseuses-and gives them all the resources they need to succeed. Even today, with a workforce of more than 23,000, Larry Page signs off on every hire. But has Google lost its innovative edge? It stumbled badly in China-Levy discloses what went wrong and how Brin disagreed with his peers on the China strategy-and now with its newest initiative, social networking, Google is chasing a successful competitor for the first time. Some employees are leaving the company for smaller, nimbler start-ups. Can the company that famously decided not to be evil still compete? No other book has ever turned Google inside out as Levy does with In the Plex.

Content

The world according to Google: biography of a search engine -- Googlenomics: cracking the code on internet profits -- Don't be evil: how Google built its culture -- Google's cloud: how Google built data centers and killed the hard drive -- Outside the box: the Google phone company. and the Google t.v. company -- Guge: Google moral dilemma in China -- Google.gov: is what's good for Google, good for government or the public? -- Epilogue: chasing tail lights: trying to crack the social code.

LCSH

Internet industry / United States

Subject

Internet industry / United States

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Abstract

It is important for education in computer science and information systems to keep up to date with the latest development in technology. With the rapid development of the Internet and the Web, many schools have included Internet-related technologies, such as Web search engines and e-commerce, as part of their curricula. Previous research has shown that it is effective to use search engine development tools to facilitate students' learning. However, the effectiveness of these tools in the classroom has not been evaluated. In this article, we review the design of three search engine development tools, SpidersRUs, Greenstone, and Alkaline, followed by an evaluation study that compared the three tools in the classroom. In the study, 33 students were divided into 13 groups and each group used the three tools to develop three independent search engines in a class project. Our evaluation results showed that SpidersRUs performed better than the two other tools in overall satisfaction and the level of knowledge gained in their learning experience when using the tools for a class project on Internet applications development.

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Abstract

The unprecedented growth of the Internet has given rise to the Dark Web, the problematic facet of the Web associated with cybercrime, hate, and extremism. Despite the need for tools to collect and analyze Dark Web forums, the covert nature of this part of the Internet makes traditional Web crawling techniques insufficient for capturing such content. In this study, we propose a novel crawling system designed to collect Dark Web forum content. The system uses a human-assisted accessibility approach to gain access to Dark Web forums. Several URL ordering features and techniques enable efficient extraction of forum postings. The system also includes an incremental crawler coupled with a recall-improvement mechanism intended to facilitate enhanced retrieval and updating of collected content. Experiments conducted to evaluate the effectiveness of the human-assisted accessibility approach and the recall-improvement-based, incremental-update procedure yielded favorable results. The human-assisted approach significantly improved access to Dark Web forums while the incremental crawler with recall improvement also outperformed standard periodic- and incremental-update approaches. Using the system, we were able to collect over 100 Dark Web forums from three regions. A case study encompassing link and content analysis of collected forums was used to illustrate the value and importance of gathering and analyzing content from such online communities.

Theme

Internet

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Abstract

Search engines are the major means of information retrieval over the Internet. People's dependence on them increases over time as SEs introduce new and sophisticated technologies. The developments in the Artificial Intelligence (AI) will transform the current search engines Artificial Intelligence Enabled Search Engines (AIESE). Search engines already play a critical role in classifying, sorting and delivering the information over the Internet. However, as Internet's mainstream role becomes more apparent and AI technology increases the sophistication of the tools of the SEs, their roles will become much more critical. Since, the future of search engines are examined, the technological singularity concept is analyzed in detail. Second and third order indirect side effects are analyzed. A four-stage evolution-model is suggested.

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RSWK

Internet / Suchmaschine / Forschung / Aufsatzsammlung

Subject

Internet / Suchmaschine / Forschung / Aufsatzsammlung

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Abstract

The widespread availability of the Internet and the variety of Internet-based applications have resulted in a significant increase in the amount of web pages. Determining the behaviors of search engine users has become a critical step in enhancing search engine performance. Search engine user behaviors can be determined by content-based or content-ignorant algorithms. Although many content-ignorant studies have been performed to automatically identify new topics, previous results have demonstrated that spelling errors can cause significant errors in topic shift estimates. In this study, we focused on minimizing the number of wrong estimates that were based on spelling errors. We developed a new hybrid algorithm combining character n-gram and neural network methodologies, and compared the experimental results with results from previous studies. For the FAST and Excite datasets, the proposed algorithm improved topic shift estimates by 6.987% and 2.639%, respectively. Moreover, we analyzed the performance of the character n-gram method in different aspects including the comparison with Levenshtein edit-distance method. The experimental results demonstrated that the character n-gram method outperformed to the Levensthein edit distance method in terms of topic identification.

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Abstract

This paper reports on a transaction log analysis of the type and topic of search queries entered into the search engine Google (Australia). Two aspects, in particular, set this apart from previous studies: the sampling and analysis take account of the distribution of search queries, and lifestyle information of the searcher was matched with each search query. A surprising finding was that there was no observed statistically significant difference in search type or topics for different segments of the online population. It was found that queries about popular culture and Ecommerce accounted for almost half of all search engine queries and that half of the queries were entered with a particular Website in mind. The findings of this study also suggest that the Internet search engine is not only an interface to information or a shortcut to Websites, it is equally a site of leisure. This study has implications for the design and evaluation of search engines as well as our understanding of search engine use.

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Abstract

Exploiting context information in a web search engine helps fine-tuning web services and applications to deliver custom-made information to end users. While context, including user and environment information, cannot be exploited efficiently in the wired Internet interaction type, it is becoming accessible with the mobile web where users have an intimate relationship with their handsets. In this type of interaction, context plays a significant role enhancing information search and therefore, allowing a search engine to detect relevant content in all digital forms and formats. This chapter proposes a context model and an architecture that promote integration of context information for individuals and social communities to add value to their interaction with the mobile web. The architecture relies on efficient knowledge management of multimedia resources for a wide range of applications and web services. The research is illustrated with a corporate case study showing how efficient context integration improves usability of a mobile search engine.

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Abstract

This study applies Kuhlthau's Information Search Process stage (ISP) model to understand bilingual users' Internet search experience. We conduct a quasi-field experiment with 30 bilingual searchers and the results suggested that the ISP model was applicable in studying searchers' information retrieval behavior in search tasks. The ISP model was applicable in studying searchers' information retrieval behavior in simple tasks. However, searchers' emotional responses differed from those of the ISP model for a complex task. By testing searchers using different search strategies, the results suggested that search engines with multilanguage search functions provide an advantage for bilingual searchers in the Internet's multilingual environment. The findings showed that when searchers used a search engine as a tool for problem solving, they might experience different feelings in each ISP stage than in searching for information for a term paper using a library. The results echo other research findings that indicate that information seeking is a multifaceted phenomenon.

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Abstract

Search Engines have become an integral part of our day to day life. Our reliance on search engines increases with every passing day. With the amount of data available on Internet increasing exponentially, it becomes important to develop new methods and tools that help to return results relevant to the queries and reduce the time spent on searching. The results should be diverse but at the same time should return results focused on the queries asked. Relation Based Page Rank [4] algorithms are considered to be the next frontier in improvement of Semantic Web Search. The probability of finding relevance in the search results as posited by the user while entering the query is used to measure the relevance. However, its application is limited by the complexity of determining relation between the terms and assigning explicit meaning to each term. Trust Rank is one of the most widely used ranking algorithms for semantic web search. Few other ranking algorithms like HITS algorithm, PageRank algorithm are also used for Semantic Web Searching. In this paper, we will provide a comparison of few ranking approaches.

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Date

17.12.2013 11:02:22

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Abstract

The main goal of this book is to transfer new research results from the fields of advanced computer sciences and information science to the design of new search engines. The readers will have a better idea of the new trends in applied research. The achievement of relevant, organized, sorted, and workable answers- to name but a few - from a search is becoming a daily need for enterprises and organizations, and, to a greater extent, for anyone. It does not consist of getting access to structural information as in standard databases; nor does it consist of searching information strictly by way of a combination of key words. It goes far beyond that. Whatever its modality, the information sought should be identified by the topics it contains, that is to say by its textual, audio, video or graphical contents. This is not a new issue. However, recent technological advances have completely changed the techniques being used. New Web technologies, the emergence of Intranet systems and the abundance of information on the Internet have created the need for efficient search and information access tools.
Recent technological progress in computer science, Web technologies, and constantly evolving information available on the Internet has drastically changed the landscape of search and access to information. Web search has significantly evolved in recent years. In the beginning, web search engines such as Google and Yahoo! were only providing search service over text documents. Aggregated search was one of the first steps to go beyond text search, and was the beginning of a new era for information seeking and retrieval. These days, new web search engines support aggregated search over a number of vertices, and blend different types of documents (e.g., images, videos) in their search results. New search engines employ advanced techniques involving machine learning, computational linguistics and psychology, user interaction and modeling, information visualization, Web engineering, artificial intelligence, distributed systems, social networks, statistical analysis, semantic analysis, and technologies over query sessions. Documents no longer exist on their own; they are connected to other documents, they are associated with users and their position in a social network, and they can be mapped onto a variety of ontologies. Similarly, retrieval tasks have become more interactive and are solidly embedded in a user's geospatial, social, and historical context. It is conjectured that new breakthroughs in information retrieval will not come from smarter algorithms that better exploit existing information sources, but from new retrieval algorithms that can intelligently use and combine new sources of contextual metadata.

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Pages

S.29-46

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Date

17. 4.2012 15:22:11

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Date

20. 1.2015 18:30:22

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20. 4.2012 13:22:37