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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.

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. Vulnerabilities in website security can be discovered through Google hacking, techniques applied to the search engine by computer criminals, identity thieves, and even terrorists to uncover secure information. This book beats Google hackers to the punch, equipping web administrators with penetration testing applications to ensure their site is invulnerable to a hacker’s search. Penetration Testing with Google Hacks explores the explosive growth of a technique known as \"Google Hacking.\" When the modern security landscape includes such heady topics as \"blind SQL injection\" and \"integer overflows,\" it's refreshing to see such a deceptively simple tool bent to achieve such amazing results; this is hacking in the purest sense of the word. Readers will learn how to torque Google to detect SQL injection points and login portals, execute port scans and CGI scans, fingerprint web servers, locate incredible information caches such as firewall and IDS logs, password databases, SQL dumps and much more - all without sending a single packet to the target! Borrowing the techniques pioneered by malicious \"Google hackers,\" this talk aims to show security practitioners how to properly protect clients from this often overlooked and dangerous form of information leakage.*First book about Google targeting IT professionals and security leaks through web browsing. *Author Johnny Long, the authority on Google hacking, will be speaking about \"Google Hacking\" at the Black Hat 2004 Briefing. His presentation on penetrating security flaws with Google is expected to create a lot of buzz and exposure for the topic. *Johnny Long's Web site hosts the largest repository of Google security exposures and is the most popular destination for security professionals who want to learn about the dark side of Google.

While virtual globes have achieved widespread popularity, from Google Earth to NASA World Wind, no single book covers the topic of globe rendering. Filling this gap, 3D Engine Design for Virtual Globes presents an in-depth treatment of rendering algorithms utilized by virtual globes. The book illustrates how to accurately render real-world data sets through core rendering algorithms for globes, terrain, imagery, and vector data. Example code, the latest book-related news, and other resources are available on a companion website.

In the beginning, the World Wide Web was exciting and open to the point of anarchy, a vast and intimidating repository of unindexed confusion. Into this creative chaos came Google with its dazzling mission--\"To organize the world's information and make it universally accessible\"--and its much-quoted motto, \"Don't be Evil.\" In this provocative book, Siva Vaidhyanathan examines the ways we have used and embraced Google--and the growing resistance to its expansion across the globe. He exposes the dark side of our Google fantasies, raising red flags about issues of intellectual property and the much-touted Google Book Search. He assesses Google's global impact, particularly in China, and explains the insidious effect of Googlization on the way we think. Finally, Vaidhyanathan proposes the construction of an Internet ecosystem designed to benefit the whole world and keep one brilliant and powerful company from falling into the \"evil\" it pledged to avoid.

In today’s world, technology has become an inevitable part of human life. In fact, during the Covid-19 pandemic, everything from the corporate world to educational institutes has shifted from offline to online. It leads to exponential increase in intrusions and attacks over the Internet-based technologies. One of the lethal threat surfacing is the Distributed Denial of Service (DDoS) attack that can cripple down Internet-based services and applications in no time. The attackers are updating their skill strategies continuously and hence elude the existing detection mechanisms. Since the volume of data generated and stored has increased manifolds, the traditional detection mechanisms are not appropriate for detecting novel DDoS attacks. This paper systematically reviews the prominent literature specifically in deep learning to detect DDoS. The authors have explored four extensively used digital libraries (IEEE, ACM, ScienceDirect, Springer) and one scholarly search engine (Google scholar) for searching the recent literature. We have analyzed the relevant studies and the results of the SLR are categorized into five main research areas: (i) the different types of DDoS attack detection deep learning approaches, (ii) the methodologies, strengths, and weaknesses of existing deep learning approaches for DDoS attacks detection (iii) benchmarked datasets and classes of attacks in datasets used in the existing literature, and (iv) the preprocessing strategies, hyperparameter values, experimental setups, and performance metrics used in the existing literature (v) the research gaps, and future directions.

In this paper, we study the effects of three different kinds of search engine rankings on consumer behavior and search engine revenues: direct ranking effect, interaction effect between ranking and product ratings, and personalized ranking effect. We combine a hierarchical Bayesian model estimated on approximately one million online sessions from Travelocity, together with randomized experiments using a real-world hotel search engine application. Our archival data analysis and randomized experiments are consistent in demonstrating the following: (1) A consumer-utility-based ranking mechanism can lead to a significant increase in overall search engine revenue. (2) Significant interplay occurs between search engine ranking and product ratings. An inferior position on the search engine affects \"higher-class\" hotels more adversely. On the other hand, hotels with a lower customer rating are more likely to benefit from being placed on the top of the screen. These findings illustrate that product search engines could benefit from directly incorporating signals from social media into their ranking algorithms. (3) Our randomized experiments also reveal that an \"active\" personalized ranking system (wherein users can interact with and customize the ranking algorithm) leads to higher clicks but lower purchase propensities and lower search engine revenue compared with a \"passive\" personalized ranking system (wherein users cannot interact with the ranking algorithm). This result suggests that providing more information during the decision-making process may lead to fewer consumer purchases because of information overload. Therefore, product search engines should not adopt personalized ranking systems by default. Overall, our study unravels the economic impact of ranking and its interaction with social media on product search engines. This paper was accepted by Lorin Hitt, information systems.

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.

Recent research suggests that search volumes of the most popular search engine worldwide, Google, provided via Google Trends, could be associated with national suicide rates in the USA, UK, and some Asian countries. However, search volumes have mostly been studied in an ad hoc fashion, without controls for spurious associations. This study evaluated the validity and utility of Google Trends search volumes for behavioral forecasting of suicide rates in the USA, Germany, Austria, and Switzerland. Suicide-related search terms were systematically collected and respective Google Trends search volumes evaluated for availability. Time spans covered 2004 to 2010 (USA, Switzerland) and 2004 to 2012 (Germany, Austria). Temporal associations of search volumes and suicide rates were investigated with time-series analyses that rigorously controlled for spurious associations. The number and reliability of analyzable search volume data increased with country size. Search volumes showed various temporal associations with suicide rates. However, associations differed both across and within countries and mostly followed no discernable patterns. The total number of significant associations roughly matched the number of expected Type I errors. These results suggest that the validity of Google Trends search volumes for behavioral forecasting of national suicide rates is low. The utility and validity of search volumes for the forecasting of suicide rates depend on two key assumptions (\"the population that conducts searches consists mostly of individuals with suicidal ideation\", \"suicide-related search behavior is strongly linked with suicidal behavior\"). We discuss strands of evidence that these two assumptions are likely not met. Implications for future research with Google Trends in the context of suicide research are also discussed.

The advent of the Internet, with sophisticated algorithmic search engines, has made accessing information as easy as lifting a finger. No longer do we have to make costly efforts to find the things we want. We can \"Google\" the old classmate, find articles online, or look up the actor who was on the tip of our tongue. The results of four studies suggest that when faced with difficult questions, people are primed to think about computers and that when people expect to have future access to information, they have lower rates of recall of the information itself and enhanced recall instead for where to access it. The Internet has become a primary form of external or transactive memory, where information is stored collectively outside ourselves.

Elasticsearch is one of the most popular tools for distributed search. This book will help you in understanding all about the new features of Elasticsearch 7, and how to use them efficiently for searching, aggregating and indexing data with speed and accuracy.