In information retrieval, dwell time denotes the time which a user spends viewing a document after clicking a link on a search engine results page (SERP).
Dwell time is the duration between when a user clicks on a search engine result, and when the user returns from that result, or is otherwise seen to have left the result. It is a relevance indicator of the search result correctly satisfying the intent of the user. Short dwell times indicate the user's query intent was not satisfied by viewing the result. Long dwell times indicate the user's query intent was satisfied. [1] Google has used dwell time in page ranking. [2]
Google Search, is a search engine provided by Google. Handling over 3.5 billion searches per day, it has a 92% share of the global search engine market. It is also the most-visited website in the world.
Search engine optimization (SEO) is the process of improving the quality and quantity of website traffic to a website or a web page from search engines. SEO targets unpaid traffic rather than direct traffic or paid traffic. Unpaid traffic may originate from different kinds of searches, including image search, video search, academic search, news search, and industry-specific vertical search engines.
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.
Click-through rate (CTR) is the ratio of users who click on a specific link to the number of total users who view a page, email, or advertisement. It is commonly used to measure the success of an online advertising campaign for a particular website as well as the effectiveness of email campaigns.
Federated search retrieves information from a variety of sources via a search application built on top of one or more search engines. A user makes a single query request which is distributed to the search engines, databases or other query engines participating in the federation. The federated search then aggregates the results that are received from the search engines for presentation to the user. Federated search can be used to integrate disparate information resources within a single large organization ("enterprise") or for the entire web.
In Web search engines, organic search results are the query results which are calculated strictly algorithmically, and not affected by advertiser payments. They are distinguished from various kinds of sponsored results, whether they are explicit pay per click advertisements, shopping results, or other results where the search engine is paid either for showing the result, or for clicks on the result.
A search engine is a software system that is designed to carry out web searches. They search the World Wide Web in a systematic way for particular information specified in a textual web search query. The search results are generally presented in a line of results, often referred to as search engine results pages (SERPs) The information may be a mix of links to web pages, images, videos, infographics, articles, research papers, and other types of files. Some search engines also mine data available in databases or open directories. Unlike web directories, which are maintained only by human editors, search engines also maintain real-time information by running an algorithm on a web crawler. Internet content that is not capable of being searched by a web search engine is generally described as the deep web.
Search Engine Results Pages (SERP) are the pages displayed by search engines in response to a query by a user. The main component of the SERP is the listing of results that are returned by the search engine in response to a keyword query.
Google Images is a search engine owned by Google that allows users to search the World Wide Web for images. It was introduced on July 12, 2001 due to a demand for pictures of the Green Versace dress of Jennifer Lopez worn in February 2000. In 2011, reverse image search functionality was added.
Relevance feedback is a feature of some information retrieval systems. The idea behind relevance feedback is to take the results that are initially returned from a given query, to gather user feedback, and to use information about whether or not those results are relevant to perform a new query. We can usefully distinguish between three types of feedback: explicit feedback, implicit feedback, and blind or "pseudo" feedback.
In Internet marketing, search advertising is a method of placing online advertisements on web pages that show results from search engine queries. Through the same search-engine advertising services, ads can also be placed on Web pages with other published content.
A web query or web search query is a query that a user enters into a web search engine to satisfy their information needs. Web search queries are distinctive in that they are often plain text and boolean search directives are rarely used. They vary greatly from standard query languages, which are governed by strict syntax rules as command languages with keyword or positional parameters.
A Web query topic classification/categorization is a problem in information science. The task is to assign a Web search query to one or more predefined categories, based on its topics. The importance of query classification is underscored by many services provided by Web search. A direct application is to provide better search result pages for users with interests of different categories. For example, the users issuing a Web query "apple" might expect to see Web pages related to the fruit apple, or they may prefer to see products or news related to the computer company. Online advertisement services can rely on the query classification results to promote different products more accurately. Search result pages can be grouped according to the categories predicted by a query classification algorithm. However, the computation of query classification is non-trivial. Different from the document classification tasks, queries submitted by Web search users are usually short and ambiguous; also the meanings of the queries are evolving over time. Therefore, query topic classification is much more difficult than traditional document classification tasks.
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.
Personalized search is web search results that are tailored specifically to an individual's interests by incorporating information about the individual beyond the specific query provided. There are two general approaches to personalizing search results, involving modifying the user's query and re-ranking search results.
Yandex Search (Яндекс) is a search engine. It is owned by Yandex, based in Russia. In January 2015, Yandex Search generated 51.2% of all of the search traffic in Russia according to LiveInternet.
Evaluation measures for an information retrieval system are used to assess how well the search results satisfied the user's query intent. Such metrics are often split into kinds: online metrics look at users' interactions with the search system, while offline metrics measure relevance, in other words how likely each result, or search engine results page (SERP) page as a whole, is to meet the information needs of the user.
User intent, otherwise known as query intent or search intent, is the identification and categorization of what a user online intended or wanted to find when they typed their search terms into an online web search engine for the purpose of search engine optimisation or conversion rate optimisation. Examples of user intent are fact-checking, comparison shopping or navigating to other websites.
Search engine privacy is a subset of internet privacy that deals with user data being collected by search engines. Both types of privacy fall under the umbrella of information privacy. Privacy concerns regarding search engines can take many forms, such as the ability for search engines to log individual search queries, browsing history, IP addresses, and cookies of users, and conducting user profiling in general. The collection of personally identifiable information (PII) of users by search engines is referred to as "tracking".
Click tracking is when user click behavior or user navigational behavior is collected in order to derive insights. Click behavior is commonly tracked using server logs which encompass click paths and clicked URLs. This log is often presented in a standard format including information like the hostname, date, and username. However, as technology develops, new software allows for in depth analysis of user click behavior using hypervideo tools. Given that the internet can be considered a risky environment, research strives to understand why users click certain links and not others. Research has also been conducted to explore the user experience of privacy with making user personal identification information individually anonymized and improving how data collection consent forms are written and structured.