Contents
Search Engines
Favorite search engines are a matter of taste, and most people these days like the favor of Google. So do I. I tend to use Google first and look elsewhere later. In most cases, Google gets me what I need. [Tip: Google search commands are explained on the More Search Help page. See also Google Search Features. To see your search history and/or to delete it, go to Google History.]
For follow-up work some searchers tend to use Bing or meta-search engines — the ones that search many other search engines at once, such as ixquick, Dogpile and Metacrawler.
Following are some specialty search engines that target certain types of content. Quality varies greatly, but sometimes these can be helpful.
Blogs: Try Clusty, Ask.com, Waypath, Technorati and/or Icerocket. The Justia Blawg Search and the Law Blog Directory search law-related blogs. The Cornell Law Library’s Legal Research Engine searches academic law blogs.
Lexis offers a fee-based general blog search (NEWS;BLOGS) or you can search blogs in various subject areas in the list of individual news publications (News & Business > Individual Publications).
Books: Google Books and Hathitrust are both designed to search the full text of large book collections. See also “Books” and “Book Stores” contents in this legal Encyclopedia.
Discussion Groups: Try Google Groups, Yahoo! Message Boards, BoardTrackerand/or Omgili.
Facebook: Open Status Search searches recent public Facebook posts. See also “Social Media and Social Networks,” below.
Government (U.S.): Try USA.gov. If you know you are looking for a “.mil,” “.gov” or “.edu” site, you can try www.SearchMil.com, www.SearchGov.com orwww.SearchEdu.com, each of which use Google technology.
Legal: The Legal Research Engine, LawRunner, Quest and LawCrawler are supposed to limit their results to legal and law-related Web sites. I have not had much success with any of them. Google Scholar searches for cases and articles if you click the “Legal opinions and journals” radio button.
Listservs: See “Discussion Groups,” above.
Medical: Try www.healthline.com.
Podcasts: Podcasts are digital audio files created in MP3 format. They can be downloaded, stored, saved and listed to at your convenience, but they aren’t necessarily easy to find. For a specialized podcast search engine try doubletwist Podcasts. If you download the free software, you can also find podcasts in the iTunes Store.
RSS Feeds: Try Feedster.
Science: Try scienceresearch.com.
Social Media and Social Networks: Try Spock, Wink, Pipl, PeekYou, and/or the more business-oriented ZoomInfo. Hshtags searches hashtags (e.g., #epicfail) across several social networks.
Twitter has its own Advanced Search, or you can try Try Topsy or TwimeMachine, which include tweets deleted from Twitter. In addition, you can search deleted tweets by the U.S. president, congress and governors using Politwoops. Hootsuite will monitor and send alerts on Twitter feeds.
For resources to track social media, see “The Internet Guide to Social Media Tracking” by Ken Kozlowski in Internet Law Researcher, Volume 19(11), p. 1 (November 2014).
See also “Facebook,” above.
Videos: Video search engines include BlinkX, Bing, and CastTV.
For more information about search engines, visit Search Engine Watch. Wikipedia posts an extensive List of Search Engines.
See Also
Internet
News
Magazines
Google
Wikipedia
Speeches
Intellectual Property in the Context of Internet Law
Read, in this legal Encyclopedia, about the topic of this section, and, specially, about Search Engines and Information Distribution Systems—Unique I.P. Issues
Intellectual Property in the Context of Internet Law
Search Engines and Information Distribution Systems-Unique I.P. Issues
An Efficient and Effective Index Structure for Query Evaluation in Search Engines, the Law and other Social Sciences
In this paper, we discuss an efficient and effective index mechanism for search engines to support both conjunctive and disjunctive queries. The main idea behind it is to decompose an inverted list into a collection of disjoint sub-lists. We will associate each word with an interval sequence, which is created by applying a kind of tree coding to a trie structure constructed over all the word sequences in a database. Then, attach each interval, instead of a word, with an inverted sub-list. In this way, both set intersection and union can be conducted by performing a series of simple interval containment checkings. Experiments have been conducted, which shows that the new index is promising. Also, how to maintain indexes, when inserting or deleting documents, is discussed in great detail.[1]
Resources
Notes and References
- Yangjun Chen, “An Efficient and Effective Index Structure for Query Evaluation in Search Engines” (Encyclopedia of Information Science and Technology, 4th Edition, Information Resources Management Association, 2018)