Search results

This paper explores resource discovery issues relating to New Zealand/Aotearoa information on the WWW in the twenty‐first century. Questions addressed are: How do New Zealand search engines compare with global search engines for finding information relating to New Zealand? Can search engines find everything that is available on the web? What are effective strategies for finding information relating to New Zealand on the web? What is the quality of NZ information on the web? What can librarians do to make NZ information more accessible on the web? Based on a study, it concludes that neither local nor global search engines are by themselves sufficient, and that to maximize retrieval a variety of engines is necessary. The NZ librarian can play a role in ensuring that NZ information is made both available and accessible. Although the paper discusses the situation in New Zealand, the results and conclusions are applicable to other countries.

This study evaluates the retrieval of New Zealand information using three local New Zealand search engines, four major global search engines and three metasearch engines. Searches for NZ topics were carried out on all the search engines, and the relative recall calculated. The local search engines did not achieve higher recall than the global search engines or metasearch engines, but no search engine achieved more than 45 percent recall. Despite the theoretical advantage of searching the databases of several individual search engines, metasearch engines did not achieve higher recall. Of relevant pages for the queries, 36 percent were outside the .nz domain. Implications for searching for geographically specific information, and for evaluation of search engines, are discussed.

Search engines usually offer a date‐restricted search on their advanced search pages. But determining the actual update of a web page is not without problems. Conducts a study testing date‐restricted queries on the search engines Google, Teoma and Yahoo! Finds that these searches fail to work properly in the engines examined. Finally, discusses implications of this for further research and search engine development.

This paper aims to give an overview of the history and evolution of commercial search engines. It traces the development of search engines from their early days to their current form as complex technology-powered systems that offer a wide range of features and services.

In recent years, advancements in artificial intelligence (AI) technology have led to the development of AI-powered chat services. This study explores official announcements and releases of three major search engines, Google, Bing and Baidu, of AI-powered chat services.

Three major players in the search engine market, Google, Microsoft and Baidu started to integrate AI chat into their search results. Google has released Bard, later upgraded to Gemini, a LaMDA-powered conversational AI service. Microsoft has launched Bing Chat, renamed later to Copilot, a GPT-powered by OpenAI search engine. The largest search engine in China, Baidu, released a similar service called Ernie. There are also new AI-based search engines, which are briefly described.

This paper discusses the strengths and weaknesses of the traditional – algorithmic powered search engines and modern search with generative AI support, and the possibilities of merging them into one service. This study stresses the types of inquiries provided to search engines, users’ habits of using search engines and the technological advantage of search engine infrastructure.

The purpose of this paper is to examine the effect of, and identify core techniques of, search engine optimization (SEO) techniques applied to the web (http://lg-sl.net) and mobile (http//m.lg-sl.net) Science Land content and services at LG Sangnam Library in Korea.

In accordance with three major SEO guidelines, ten SEO techniques were identified and applied, and their implications were extracted on three areas: improved search engine accessibility, increased relevance between site content and search engine keywords, and improved site credibility. The effects were quantitatively analyzed in terms of registered search engine keywords and influx of visits via search engines.

This study shows that SEO techniques help increase the exposure of the library services and the number of visitors through search engines.

SEO techniques have been applied to a few non-Korean information service organizations, but it is not a well-accepted practice in Korean libraries. And the dominant search engines in Korea have published their own SEO guidelines. Prior to this study, no significant endeavors have been undertaken in the context of Korean library services that have adopted SEO techniques to boost exposure of library services and increase user traffics.

This is the first published study that has applied optimized SEO techniques to Korean web and mobile library services, in order to demonstrate the usefulness of the techniques for maximized exposure of library content.

Pay for performance (PFP) search engines provide search services for documents on the Web, but unlike traditional search engines, they rank documents not on content characteristics, but according to the amount of money the owner of a Web site is willing to pay if a user visits the Web site through the search results pages. A study was conducted to compare the retrieval effectiveness of Overture (a PFP search engine) and Google (a traditional search engine) using a test suite of general knowledge questions. A total of 45 queries, based on a popular game show, “Who wants to be a millionaire?”, were submitted to each of these search engines and the first ten documents returned were analysed using different relevancy criteria. Results indicated that Google outperformed Overture in terms of precision and number of queries that could be answered. Implications for this study are also discussed.

This paper reports the findings of a major study examining the overlap among results retrieved by three major web search engines. The goal of the research was to: measure the overlap across three major web search engines on the first results page overlap (i.e. share the same results) and the differences across a wide range of user defined search terms; determine the differences in the first page of search results and their rankings (each web search engine's view of the most relevant content) across single‐source web search engines, including both sponsored and non‐sponsored results; and measure the degree to which a meta‐search web engine, such as Dogpile.com, provides searchers with the most highly ranked search results from three major single source web search engines.

The authors collected 10,316 random Dogpile.com queries and ran an overlap algorithm using the URL for each result by query. The overlap of first result page search for each query was then summarized across all 10,316 to determine the overall overlap metrics. For a given query, the URL of each result for each engine was retrieved from the database.

The percent of total results unique retrieved by only one of the three major web search engines was 85 percent, retrieved by two web search engines was 12 percent, and retrieved by all three web search engines was 3 percent. This small level of overlap reflects major differences in web search engines retrieval and ranking results.

This study provides an important contribution to the web research literature. The findings point to the value of meta‐search engines in web retrieval to overcome the biases of single search engines.

The results of this research can inform people and organizations that seek to use the web as part of their information seeking efforts, and the design of web search engines.

This research is a large investigation into web search engine overlap using real data from a major web meta‐search engine and single web search engines that sheds light on the uniqueness of top results retrieved by web search engines.

To describe a small‐scale quantitative evaluation of the scholarly information search engine, Google Scholar.

Google Scholar's ability to retrieve scholarly information was compared to that of three popular search engines: Ask.com, Google and Yahoo! Test queries were presented to all four search engines and the following measures were used to compare them: precision; Vaughan's Quality of Result Ranking; relative recall; and Vaughan's Ability to Retrieve Top Ranked Pages.

Significant differences were found in the ability to retrieve top ranked pages between Ask.com and Google and between Ask.com and Google Scholar for scientific queries. No other significant differences were found between the search engines. This may be due to the relatively small sample size of eight queries. Results suggest that, for scientific queries, Google Scholar has the highest precision, relative recall and Ability to Retrieve Top Ranked Pages. However, it achieved the lowest score for these three measures for non‐scientific queries. The best overall score for all four measures was achieved by Google. Vaughan's Quality of Result Ranking found a significant correlation between Google and scientific queries.

As with any search engine evaluation, the results pertain only to performance at the time of the study and must be considered in light of any subsequent changes in the search engine's configuration or functioning. Also, the relatively small sample size limits the scope of the study's findings.

These results suggest that, although Google Scholar may prove useful to those in scientific disciplines, further development is necessary if it is to be useful to the scholarly community in general.

This is a preliminary study in applying the accepted performance measures of precision and recall to Google Scholar. It provides information specialists and users with an objective evaluation of Google Scholar's abilities across both scientific and non‐scientific disciplines and paves the way for a larger study.

This paper evaluates the precision of four metasearch engines (MSEs) – DuckDuckGo, Dogpile, Metacrawler and Startpage, to determine which metasearch engine exhibits the highest level of precision and to identify the metasearch engine that is most likely to return the most relevant search results.

The research is divided into two parts: the first phase involves four queries categorized into two segments (4-Q-2-S), while the second phase includes six queries divided into three segments (6-Q-3-S). These queries vary in complexity, falling into three types: simple, phrase and complex. The precision, average precision and the presence of duplicates across all the evaluated metasearch engines are determined.

The study clearly demonstrated that Startpage returned the most relevant results and achieved the highest precision (0.98) among the four MSEs. Conversely, DuckDuckGo exhibited consistent performance across both phases of the study.

The study only evaluated four metasearch engines, which may not be representative of all available metasearch engines. Additionally, a limited number of queries were used, which may not be sufficient to generalize the findings to all types of queries.

The findings of this study can be valuable for accreditation agencies in managing duplicates, improving their search capabilities and obtaining more relevant and precise results. These findings can also assist users in selecting the best metasearch engine based on precision rather than interface.

The study is the first of its kind which evaluates the four metasearch engines. No similar study has been conducted in the past to measure the performance of metasearch engines.

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 Web searching.

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.

Research limitations/implications — The chapter suggests a basis for research in the field and also introduces further research directions.

Originality/value of paper — The chapter gives a concise overview of the topics dealt within the book and also shows directions for researchers interested in Web search engines.