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Researching serendipity in digital information environments
Chance, luck, and good fortune are the usual go-to descriptors of serendipity, a phenomenon aptly often coupled with famous anecdotes of accidental discoveries in engineering and science in modern history such as penicillin, Teflon, and Post-it notes. Serendipity, however, is evident in many fields of research, in organizations, in everyday life--and there is more to it than luck implies. While the phenomenon is strongly associated with in-person interactions with people, places, and things, most attention of late has focused on its preservation and facilitation within digital information environments. Serendipity's association with unexpected, positive user experiences and outcomes has spurred an interest in understanding both how current digital information environments support serendipity and how novel approaches may be developed to facilitate it. Research has sought to understand serendipity, how it is manifested in people's personality traits and behaviors, how it may be facilitated in digital information environments such as mobile applications, and its impacts on an individual, an organizational, and a wider level. Because serendipity is expressed and understood in different ways in different contexts, multiple methods have been used to study the phenomenon and evaluate digital information environments that may support it. This volume brings together different disciplinary perspectives and examines the motivations for studying serendipity, the various ways in which serendipity has been approached in the research, methodological approaches to build theory, and how it may be facilitated. Finally, a roadmap for serendipity research is drawn by integrating key points from this volume to produce a framework for the examination of serendipity in digital information environments.
Book
To the problem of controlled guaranteed search for a mobile object on the plane
The problem of guaranteed search for an object moving on a horizontal plane, the initial state of which is known up to a given set, is considered. An object controlled by acceleration in space is carried out the search. It is shown that, based on the minimax approach, the considering problem is reduced to a problem of bounded control with a moving right end. Using the generalized Kalman’s method in an explicit form, formulas are obtained that make it possible to calculate bounded guaranteeing controls and the guaranteed search time. The results of numerical calculation are brought.
Journal Article
PostGIS in action
\"PostGIS in Action, Second Edition teaches you to solve real-world goedata problems. It first gives you a background in vector-, raster-, and topology-based GIS and then quickly moves into analyzing, viewing, and mapping data. You'll learn how to optimize queries for maximum speed, simplify geometrics for greater efficiency, and create custom functions for your own applications. You'll also learn how to apply your existing GIS knowledge to PostGIS and integrate with other GIS tools. What's Inside: An introduction to spatial databases -- geometry, geography, raster, and topology spatial types, functions, and queries -- Applying PostGIS to real-world problems -- Extending PostGIS to web and desktop applications -- Updated for PostGIS 2.x and PostgreSQL 9.x\"--Back cover.
Book
Numerical Algorithms for Personalized Search in Self-organizing Information Networks
This book lays out the theoretical groundwork for personalized search and reputation management, both on the Web and in peer-to-peer and social networks. Representing much of the foundational research in this field, the book develops scalable algorithms that exploit the graphlike properties underlying personalized search and reputation management, and delves into realistic scenarios regarding Web-scale data.
Sep Kamvar focuses on eigenvector-based techniques in Web search, introducing a personalized variant of Google's PageRank algorithm, and he outlines algorithms--such as the now-famous quadratic extrapolation technique--that speed up computation, making personalized PageRank feasible. Kamvar suggests that Power Method-related techniques ultimately should be the basis for improving the PageRank algorithm, and he presents algorithms that exploit the convergence behavior of individual components of the PageRank vector. Kamvar then extends the ideas of reputation management and personalized search to distributed networks like peer-to-peer and social networks. He highlights locality and computational considerations related to the structure of the network, and considers such unique issues as malicious peers. He describes the EigenTrust algorithm and applies various PageRank concepts to P2P settings. Discussion chapters summarizing results conclude the book's two main sections.
Clear and thorough, this book provides an authoritative look at central innovations in search for all of those interested in the subject.
eBook
A Progressive and Joint Method for Micro and Macro Architecture Search
Recently, neural architecture search (NAS) has achieved great success in design neural architectures automatically. Differentiable architecture search (DARTS) has succeeded in reducing computational cost and making the searching process efficient. Based on the cell-based search space in DARTS, we extend the search space by searching diverse cells at different stages and various connection between cells. We also use a progressive and joint method to search the micro and macro architecture together. Extensive experiments on CIFAR-10 demostrate that we can obtain a better result than the original search space.
Journal Article
Algorithms of Oppression
A revealing look at how negative biases against women of color are embedded in search engine results and algorithms
Run a Google search for \"black girls\"—what will you find? \"Big Booty\" and other sexually explicit terms are likely to come up as top search terms. But, if you type in \"white girls,\" the results are radically different. The suggested porn sites and un-moderated discussions about \"why black women are so sassy\" or \"why black women are so angry\" presents a disturbing portrait of black womanhood in modern society.
In Algorithms of Oppression, Safiya Umoja Noble challenges the idea that search engines like Google offer an equal playing field for all forms of ideas, identities, and activities. Data discrimination is a real social problem; Noble argues that the combination of private interests in promoting certain sites, along with the monopoly status of a relatively small number of Internet search engines, leads to a biased set of search algorithms that privilege whiteness and discriminate against people of color, specifically women of color.
Through an analysis of textual and media searches as well as extensive research on paid online advertising, Noble exposes a culture of racism and sexism in the way discoverability is created online. As search engines and their related companies grow in importance—operating as a source for email, a major vehicle for primary and secondary school learning, and beyond—understanding and reversing these disquieting trends and discriminatory practices is of utmost importance.
An original, surprising and, at times, disturbing account of bias on the internet, Algorithms of Oppression contributes to our understanding of how racism is created, maintained, and disseminated in the 21st century.
eBook
Strategic searches using digital tools
Readers will get a step-by-step overview of how to make the most of their search activities so they can get the information they want and need with just a few keystrokes, swipes, or clicks.
Book
Mastering Apache Solr 7.x
Apache Solr is the only standalone enterprise search server with a REST-like application interface. providing highly scalable, distributed search and index replication for many of the world's largest internet sites. To begin with, you would be introduced to how you perform full text search, multiple filter search, perform dynamic clustering and so on helping you to brush up the basics of Apache Solr. You will also explore the new features and advanced options released in Apache Solr 7.x which will get you numerous performance aspects and making data investigation simpler, easier and powerful. You will learn to build complex queries, extensive filters and how are they compiled in your system to bring relevance in your search tools. You will learn to carry out Solr scoring, elements affecting the document score and how you can optimize or tune the score for the application at hand. You will learn to extract features of documents, writing complex queries in re-ranking the documents. You will also learn advanced options helping you to know what content is indexed and how the extracted content is indexed. Throughout the book, you would go through complex problems with solutions along with varied approaches to tackle your business needs. By the end of this book, you will gain advanced proficiency to build out-of-box smart search solutions for your enterprise demands.
eBook