Keyword Search Quieries

Bi et al \cite{Rec:Bi} provides ranked related entities to the user query along with the results of the main entity. In order to do this, this articles makes use of user's search history, click history and knowledge base. A matrix is created comprising of the user information which connects to the entities along with the ranking, click results. A tri-linear function\cite{Rec:Bi} is defined mapping these details and which will be used to rank the related entities

With the advent of computer technology in 1990’s the need to search large databases was increasingly becoming vital. The search engines prior to PageRank had limitations, the then most widely used algorithm used text based indexes to provide search results on World Wide Web however had limitations of improper search results as the logic used by the search engines looked at the number of occurrences of the search word in webpage which sometimes resulted in improper search results. Another technique used during the time was based on variations of standard vector space model – i.e. search based on how recent the webpage was updated and/or how close the search terms are to the

Law enforcement officers across the country have undergone extensive training and have been entrusted with powers to protect the public. They have every right to remain vigilant in conducting their job to ensure their safety as well as the publics. They are authorized to conduct specific types of searches with out a warrant and three types of searches are: plain view search, consent to search, and stop and frisk. We will look at each type of search closer and attempt to throughly describe each. A plain-view search is a tool an officer can utilize to legally confiscate or seize a specific item. This type of search requires the officer: to view the item while he or she is in the immediate area, recogize and realize the item can be seized,

Have you ever actually tried finding a needle in a haystack? Not in a proverbial sense — everyone’s done that, but an actual, physical piece of metal often used for sewing? If you have, feel free to stop reading. Light this paper on fire if you’ve got the urge, make a paper airplane, keep reading, whatever floats your boat. But for those of you who haven’t, allow me, a seasoned haystack searcher, to provide you with some insight on the matter.

There are many challenges that I am facing while searching data using the online Olivet library. I am using the Boolean operators, which are “used in electronic databases and other search engines to define the relationships between keywords or phrases” (Bui, 2014, p. 59).

I am surprised for my performance on this GTW because I only have two errors in total and none of them is a global error. However, I keep having same error from the first GTW, even in the latest GTW: word choice. I believe word choice has become an annoying for my writings because it appears again and again in my writing. Though it is not a serious problem for the whole writing, it reflects the problem that I have the wrong definition for wordings, or I can’t determine the appropriate words for the sentences. Totally, I have a weak word bank, which means I need to expand my understanding on more

(King-Lup Liu, 2001) Given countless motors on the Internet, it is troublesome for a man to figure out which web search tools could serve his/her data needs. A typical arrangement is to build a metasearch motor on top of the web indexes. After accepting a client question, the metasearch motor sends it to those fundamental web indexes which are liable to give back the craved archives for the inquiry. The determination calculation utilized by a metasearch motor to figure out if a web index ought to be sent the inquiry ordinarily settles on the choice in light of the web search tool agent, which contains trademark data about the database of a web search tool. Be that as it may, a hidden web index may not will to give the required data to the metasearch motor. This paper demonstrates that the required data can be evaluated from an uncooperative web crawler with great exactness. Two bits of data which license precise web crawler determination are the quantity of reports filed by the web index and the greatest weight of every term. In this paper, we display systems for the estimation of these two bits of data.

Whenever you are writing an SEO-friendly article, Webpage content or essay keyword plays a crucial role. A keyword density checker is a tool to calculate the occurrence of the important keyword in your webpage or any content so that you can verify whether the keywords are appearing as desired.

Text Retrieval and techniques are modified by many commercial and many open sources in the domain of information retrieval. Text retrieval refers to the process of searching for texts, information within collections, or metadata about documents. It is assigned to answer for relevant documents, not just simple matches to patterns. When considering indexing and searching applications, users may find and consider among many products available on the market. Mainly, the products can be grouped into two categories. The first of these categories are information retrieval libraries that can be easily developed and embedded into application. The second consists of ready to apply indexing and searching applications that are basically designed to work with particular types of data, and are therefore less flexible (Molková 2011). Some of the famous libraries cover text retrieval topic are introduced in next section.

Made out of Web locales interconnected by hyperlinks, the World Wide Web can be seen as an enormous yet tumultuous wellspring of data. For choice making numerous business applications need to rely on upon web keeping in mind the end goal to total data from various sites. Programmed information extraction assumes an essential part in preparing results gave via internet searchers in the wake of presenting the question by client. presently days "site" has begun keeping more significance to our life. without which it is hard to oblige even one day .so it has turned into the need that the site ought to be more enlightening and alluring . be that as it may, the sites are created and just grew purposely or unwittingly

The main aim of this project is to research on the integration of “Natural Language Processing “ and information systems engineering to enhance query retrieval in natural language processing.

A person’s name is the one thing that cannot be taken away from him or her. It is the only thing that stays with us from the day we are born until the day we take our last breath. Emily Annabelle Pierce is the name given to me by my parents. I did not choose this name or change it in any way. My parents named me this before they knew me, but my names parallel a lot with my character.

Search EnginesA search engine is a software system designed to search for information on the World Wide Web. This information is usually categorised into websites, images, videos and shopping results.Examples of search enginesGoogleGoogle is the world’s most popular website and uses many different algorithms to produce search results. BingBing is a search engine from Microsoft that comes as standard on Windows and Internet Explorer. DuckDuckGoDuckDuckGo is an alternative search engine which boasts privacy. There is no way to sign in and they do not track searches or users.Meta TagsMeta tags provide search engines with information about the site and specific pages. They are added to the <head> tag.The description attribute will allow the site owner to define the short description that shows under their search result on a search engine.The content attribute allows the site owner to define keywords so that when a customer searches for the keywords the retailer. The more keywords that match, the higher up the retailer is in the search results.Other ads are shown lower down as they did not bid as much.Google produces a list of shopping results. The companies also bid for spots hereThe top three search results are text advertisements. Sony has paid the most so they are on the top of the listFrom there, I clicked on one of the shopping results which took me to the product page. From there I can learn more about the product or pre-order it.CrawlersCrawlers (or Spiders) are the names

If we search for an answer to a question in a typical search engines such as Google, Bing, or Yahoo, it usually gives us relevant pages based on the key words in the query. We may need to follow several links or pages to reach a document providing a relevant answer. If we can store such search pathways to an answer for a given user query and reuse it for future searches it may speed up this process. Our question answering system motivated by reuse of prior web search pathways to yield an answer a user query. We represent queries and search pathways in a semi-structured format that contains query terms and referenced classes within a realm based ontology. First part of my research is to build a system that can automatically tag the terms in a user query to relevant classes from a domain-based ontology. The other part is to rank the prior searches (contains user queries, assigned classes, and search pathways) stored in the database based on the

Query processor system parses the query and interprets the meaning of the end-user’s query terms. This enables the construction of a meaningful query. Before any actual query re-formulation, the mapping between the vocabulary of the ontologies and the query is required. The mapping is indispensable for retrieval improvement using ontology based query approaches. The first step of the processor is to identify the set of ontologies likely to provide the information requested by the user. Hence it searches for near syntactic matches within the ontology indexes, using lexically related words obtained from WordNet [27] and from the ontologies, used as background knowledge sources. It identifies the subject, predicate and object, which is used to generate the DL query and runs it against the ontology to attempt to