Searching Website Resources
- In google search results, copy the original search string and ^F to show it on the page.
- For exact phrase match, enclose in quotes.
- Use “-name” to skip name.
- Add “htm” for web pages first.
- Use “site:name“ to search only that site.
- See > Google Search Help
Internet Searching Literature, Procedures and Tools
Web search engines work by storing information about many web pages, which they retrieve from the HTML markup of the pages. These pages are retrieved by a Web crawler (sometimes also known as a spider) — an automated Web crawler which follows every link on the site. The site owner can exclude specific pagesby using robots.txt.
Symposium on Human-Computer Interaction and Information Retrieval
Human-computer Information Retrieval (HCIR) combines research from the fields of human-computer interaction (HCI) and information retrieval (IR), placing an emphasis on human involvement in search activities. The event unites academic researchers and industrial practitioners working at the intersection of HCI and IR to develop more sophisticated models, tools, and evaluation metrics to support activities such as interactive information retrieval and exploratory search.
All the information in the world is online, but sometimes a simple Google search doesn’t give you the results you want. These modules will show you how to effectively find information online and evaluate its quality, thus improving your information literacy.
Search engine bias and Customized results
Although search engines are programmed to rank websites based on some combination of their popularity and relevancy, empirical studies indicate various political, economic, and social biases in the information they provide. Many search engines such as Google and Bing provide customized results based on the user’s activity history. This leads to an effect that has been called a filter bubble.
Search Engine Showdown, the users’ guide to Web searching, compares and evaluates Internet search engines from the searcher’s perspective. Developed originally as a way to keep track of search engine features and search capabilities and to share that information with others, the site has evolved over the years as search engines themselves have changes. It includes search engine news and the occasional analysis.
Semantic search seeks to improve search accuracy by understanding searcher intent and the contextual meaning of terms as they appear in the searchable dataspace, whether on the Web or within a closed system, to generate more relevant results. Author Seth Grimes lists “11 approaches that join semantics to search”, and Hildebrand et al. provide an overview that lists semantic search systems and identifies other uses of semantics in the search process. Semantic search systems consider various points including context of search, location, intent, variation of words, synonyms, generalized and specialized queries, concept matching and natural language queries to provide relevant search results. Major web search engines like Google and Bing incorporate some elements of semantic search
Activities such as Web Services and the Semantic Web are working to create a web of distributed machine understandable data. In this paper we present an application called ‘Semantic Search’ which is built on these supporting technologies and is designed to improve traditional web searching. We provide an overview of TAP, the application framework upon which the Semantic Search is built.