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SLATES (Search, Links, Authorship, Tags, Extensions, Signalling) is an initialism that describes the business impacting capabilities, derived from the effective use of Web 2.0 technologies in and across enterprises. [1]
This acronym refers to the key elements in the phenomena often referred to as Enterprise 2.0, which was defined by Professor Andrew McAfee as “the use of emergent social software platforms within companies, or between companies and their partners or customers” [1]
Search is traditionally defined as "A web search query is a query that a user enters into web search engine to satisfy their information needs. Web search queries are distinctive in that they are unstructured and often ambiguous; they vary greatly from standard query languages which are governed by strict syntax rules."[ who? ] The term in the context of SLATES refers to effective use of such search queries in and across enterprise boundaries, for example being able to enhance the "discoverability of information which drives re-use, leverage and ROI".
Links are the use of links or uniform resource identifiers to forge deep interconnections between the information content across collaborating enterprises.
Authorship is the ability of all individuals within and across enterprises to easily publish content accessible across collaborating enterprises.
Tags is the use of tags to enable the rapid and humanistic organisation of data across collaborating enterprises.
Extensions are the mining of previously gathered data relating to a users activities or transactions which allows users to be guided to initiate other valuable activities or transactions. Exemplified by the phrase "other customers who purchased this book also purchased these books"
Signalling involves the sending of alerts to users of the changing state of an element of interest i.e. using RSS. Exemplified by the Online Status of other users in instant messaging clients
Meta elements are tags used in HTML and XHTML documents to provide structured metadata about a Web page. They are part of a web page's head section. Multiple Meta elements with different attributes can be used on the same page. Meta elements can be used to specify page description, keywords and any other metadata not provided through the other head elements and attributes.
Wiki software is collaborative software that runs a wiki, which allows users to create and collaboratively edit "pages" or entries via a web browser. A wiki system is usually a web application that runs on one or more web servers. The content, including previous revisions, is usually stored in either a file system or a database. Wikis are a type of web content management system, and the most commonly supported off-the-shelf software that web hosting facilities offer.
In digital marketing and online advertising, spamdexing is the deliberate manipulation of search engine indexes. It involves a number of methods, such as link building and repeating unrelated phrases, to manipulate the relevance or prominence of resources indexed, in a manner inconsistent with the purpose of the indexing system.
Search engine optimization (SEO) is the process of increasing the quality and quantity of website traffic by increasing the visibility of a website or a web page to users of a web search engine.
Social software, also known as social apps, include communication and interactive tools often based on the Internet. Communication tools typically handle the capturing, storing and presentation of communication, usually written but increasingly including audio and video as well. Interactive tools handle mediated interactions between a pair or group of users. They focus on establishing and maintaining a connection among users, facilitating the mechanics of conversation and talk. Social software generally refers to software that makes collaborative behaviour, the organisation and moulding of communities, self-expression, social interaction and feedback possible for individuals. Another element of the existing definition of social software is that it allows for the structured mediation of opinion between people, in a centralized or self-regulating manner. The most improved area for social software is that Web 2.0 applications can all promote cooperation between people and the creation of online communities more than ever before.
A metasearch engine is an online Information retrieval tool that uses the data of a web search engine to produce its own results. Metasearch engines take input from a user and immediately query search engines for results. Sufficient data is gathered, ranked, and presented to the users.
Web mining is the application of data mining techniques to discover patterns from the World Wide Web. As the name proposes, this is information gathered by mining the web. It makes utilization of automated apparatuses to reveal and extricate data from servers and web2 reports, and it permits organizations to get to both organized and unstructured information from browser activities, server logs, website and link structure, page content and different sources.
Social computing is an area of computer science that is concerned with the intersection of social behavior and computational systems. It is based on creating or recreating social conventions and social contexts through the use of software and technology. Thus, blogs, email, instant messaging, social network services, wikis, social bookmarking and other instances of what is often called social software illustrate ideas from social computing.
Web 2.0 refers to websites that emphasize user-generated content, ease of use, participatory culture and interoperability for end users.
XWiki is a free wiki software platform written in Java with a design emphasis on extensibility. XWiki is an enterprise wiki. It includes WYSIWYG editing, OpenDocument based document import/export, semantic annotations and tagging, and advanced permissions management.
Enterprise social software, comprises social software as used in "enterprise" (business/commercial) contexts. It includes social and networked modifications to corporate intranets and other classic software platforms used by large companies to organize their communication. In contrast to traditional enterprise software, which imposes structure prior to use, enterprise social software tends to encourage use prior to providing structure.
Social search is a behavior of retrieving and searching on a social searching engine that mainly searches user-generated content such as news, videos and images related search queries on social media like Facebook, LinkedIn, Twitter, Instagram and Flickr. It is an enhanced version of web search that combines traditional algorithms. The idea behind social search is that instead of ranking search results purely based on semantic relevance between a query and the results, a social search system also takes into account social relationships between the results and the searcher. The social relationships could be in various forms. For example, in LinkedIn people search engine, the social relationships include social connections between searcher and each result, whether or not they are in the same industries, work for the same companies, belong the same social groups, and go the same schools, etc.
Traction TeamPage is a proprietary enterprise 2.0 social software product developed by Traction Software Inc of Providence, Rhode Island.
Enterprise search is the practice of making content from multiple enterprise-type sources, such as databases and intranets, searchable to a defined audience.
SharePoint is a web-based collaborative platform that integrates with Microsoft Office. Launched in 2001, SharePoint is primarily sold as a document management and storage system, but the product is highly configurable and usage varies substantially among organizations.
A Visual Search Engine is a search engine designed to search for information on the World Wide Web through the input of an image or a search engine with a visual display of the search results. Information may consist of web pages, locations, other images and other types of documents. This type of search engines is mostly used to search on the mobile Internet through an image of an unknown object. Examples are buildings in a foreign city. These search engines often use techniques for Content Based Image Retrieval.
Collaborative search engines (CSE) are Web search engines and enterprise searches within company intranets that let users combine their efforts in information retrieval (IR) activities, share information resources collaboratively using knowledge tags, and allow experts to guide less experienced people through their searches. Collaboration partners do so by providing query terms, collective tagging, adding comments or opinions, rating search results, and links clicked of former (successful) IR activities to users having the same or a related information need.
Folksonomy is a classification system in which end users apply public tags to online items, typically to make those items easier for themselves or others to find later. Over time, this can give rise to a classification system based on those tags and how often they are applied or searched for, in contrast to a taxonomic classification designed by the owners of the content and specified when it is published. This practice is also known as collaborative tagging, social classification, social indexing, and social tagging. Folksonomy was originally "the result of personal free tagging of information [...] for one's own retrieval", but online sharing and interaction expanded it into collaborative forms. Social tagging is the application of tags in an open online environment where the tags of other users are available to others. Collaborative tagging is tagging performed by a group of users. This type of folksonomy is commonly used in cooperative and collaborative projects such as research, content repositories, and social bookmarking.
Search-based applications are software applications in which a search engine platform is used as the core infrastructure for information access and reporting. Search-based applications use semantic technologies to aggregate, normalize and classify unstructured, semi-structured and/or structured content across multiple repositories, and employ natural language technologies for accessing the aggregated information.
The following outline is provided as an overview of and topical guide to search engines.
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