New perspectives on Web search engine research

Purpose–The purpose of this chapter is to give an overview of the context of Web search and search engine-related research, as well as to introduce the reader to the sections and chapters of the book. Methodology/approach–We review literature dealing with various aspects of search engines, with special emphasis on emerging areas of Web searching, search engine evaluation going beyond traditional methods, and new perspectives on Webs earching. Findings–The approaches to studying Web search engines are manifold. Given the importance of Web search engines for knowledge acquisition, research from different perspectives needs to be integrated into a more cohesive perspective. Researchlimitations/implications–The chapter suggests a basis for research in the field and also introduces further research directions. Originality/valueofpaper–The chapter gives a concise overview of the topics dealt with in the book and also shows directions for researchers interested in Web search engines

New perspectives on Web search engine research

Purpose–The purpose of this chapter is to give an overview of the context of Web search and search engine-related research, as well as to introduce the reader to the sections and chapters of the book. Methodology/approach–We review literature dealing with various aspects of search engines, with special emphasis on emerging areas of Web searching, search engine evaluation going beyond traditional methods, and new perspectives on Webs earching. Findings–The approaches to studying Web search engines are manifold. Given the importance of Web search engines for knowledge acquisition, research from different perspectives needs to be integrated into a more cohesive perspective. Researchlimitations/implications–The chapter suggests a basis for research in the field and also introduces further research directions. Originality/valueofpaper–The chapter gives a concise overview of the topics dealt with in the book and also shows directions for researchers interested in Web search engines

Evaluating the retrieval effectiveness of Web search engines using a representative query sample

Search engine retrieval effectiveness studies are usually small-scale, using only limited query samples. Furthermore, queries are selected by the researchers. We address these issues by taking a random representative sample of 1,000 informational and 1,000 navigational queries from a major German search engine and comparing Google's and Bing's results based on this sample. Jurors were found through crowdsourcing, data was collected using specialised software, the Relevance Assessment Tool (RAT). We found that while Google outperforms Bing in both query types, the difference in the performance for informational queries was rather low. However, for navigational queries, Google found the correct answer in 95.3 per cent of cases whereas Bing only found the correct answer 76.6 per cent of the time. We conclude that search engine performance on navigational queries is of great importance, as users in this case can clearly identify queries that have returned correct results. So, performance on this query type may contribute to explaining user satisfaction with search engines

Credibility in Web Search Engines

Web search engines apply a variety of ranking signals to achieve user satisfaction, i.e., results pages that provide the best-possible results to the user. While these ranking signals implicitly consider credibility (e.g., by measuring popularity), explicit measures of credibility are not applied. In this chapter, credibility in Web search engines is discussed in a broad context: credibility as a measure for including documents in a search engine's index, credibility as a ranking signal, credibility in the context of universal search results, and the possibility of using credibility as an explicit measure for ranking purposes. It is found that while search engines-at least to a certain extent-show credible results to their users, there is no fully integrated credibility framework for Web search engines

Getting Bulk Data Through Google: An empirical study

To store the information in a database is one of the major tasks. The efficient storage of data is important for future use. Information retrieval is a method of gathering information related to input queries from the various sources or stored databases. To retrieve the information, a search engine plays an important role. A web search engine creates an index to match queries. The quality of information is improved with the help of search engine. For retrieving the information, a search engine comprises some modules such as query processor, a searching and matching function, document processor and page rank capability. This paper focuses on the retrieval of web documents against input queries and stores them in to database. A Google search API can be used to fetch the results. It analyses the data by processing through these modules and downloads the content available in different formats

Diversification Based Static Index Pruning - Application to Temporal Collections

Nowadays, web archives preserve the history of large portions of the web. As medias are shifting from printed to digital editions, accessing these huge information sources is drawing increasingly more attention from national and international institutions, as well as from the research community. These collections are intrinsically big, leading to index files that do not fit into the memory and an increase query response time. Decreasing the index size is a direct way to decrease this query response time. Static index pruning methods reduce the size of indexes by removing a part of the postings. In the context of web archives, it is necessary to remove postings while preserving the temporal diversity of the archive. None of the existing pruning approaches take (temporal) diversification into account. In this paper, we propose a diversification-based static index pruning method. It differs from the existing pruning approaches by integrating diversification within the pruning context. We aim at pruning the index while preserving retrieval effectiveness and diversity by pruning while maximizing a given IR evaluation metric like DCG. We show how to apply this approach in the context of web archives. Finally, we show on two collections that search effectiveness in temporal collections after pruning can be improved using our approach rather than diversity oblivious approaches

Information Consumer or Product?: Algorithmic Literacy

A brief essay of the importance of being aware of your online privacy, algorithm bias, filter bubbles, and the sale online personal data. A starting place with provide resources to be a better user of the internet and more informed information consumer

Beyond Search: A Technology Probe Investigation

Purpose — We assert that researchers developing new web interaction tools should consider an array of user motives beyond query-based information retrieval. This chapter reports on two probes used to investigate user activities that go beyond search as traditionally conceived. Design/methodology — This chapter reviews research on user experiences with search engines and general web use. It then describes the design and case study of cards and pebbles, two search engine-based probes developed to help elicit new concepts for web-based experiences. Findings — Participants reflect on their experiences with the probes and offer ideas regarding how to incrementally shift the traditional search paradigm and conceive of the web in new ways. Implications/value — This investigation serves as a starting point by offering criteria that should be considered when designing new ‘beyond search’ tools

Search Engine Optimization (SEO) As A Promotional Media On Google Search

the current era, people's interest in using the internet is getting higher, this is because internet media has become an informative tool that can be accessed at any time. In searching for information, internet users usually use search engines. One of them is Google, the most widely used search engine. To find information in the Google search engine, we must use keywords. With SEO technique the website will be easy to find. A website optimization based on keywords, its implementation using On-page SEO and Off-page SEO mechanisms. On-page SEO is changing web pages according to the target keywords. By paying attention to important elements such as meta title, meta description, heading tags, text format, alt text, content, robot.txt, and sitemap.xml. Off-page SEO is a method that is carried out outside the website, creating relevant backlinks to the targeted website. This method can make the website as an organic promotional medium that brings traffic. In this research applying the concept of SEO both On-page and Off-page, the results obtained that there was a significant increase in traffic and based on the results of using the User Acceptance Test (UAT) with five aspects of component quality, this SEO support system can help in analyzing the website and as many as 82.3% of respondents said that the system built was very goo