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propose a """"Hybrid Search Engine Framework for the Internet of Things based on Spatial-Temporal, Value-based, and Keyword-based Conditions"""" (""""IoT-SVK Search Engine"""" for short). The experimental results
The success of the search engine may be our Newtonian paradigm for the Web. It enables us to do so much information discovery that it is difficult to imagine what we cannot do with it.
issued to the databases also contain spatial and textual components, for example, "Find shelters with emergency medical facilities in Orange County," or "Find earthquake-prone zones in Southern California." We refer to such queries as spatial-keyword queries or SK queries for short. In recent times, a lot of interest has
Keyword auctions are being used to sell the positions along the side of organic results shown by search engine when user types a keyword or a query related to keyword in a search engine. It has been a huge revenue generating arena for search engines since last decade. Irrespective of the great success of these types
This paper presents a keyword extraction technique that can be used for tracking topics over time. In our work, keywords are a set of significant words in an article that gives high-level description of its contents to readers. Identifying keywords from a large amount of on-line news data is very useful in that it can
quality of information retrieval. The contributions of our research are twofold. First, the existing ranking algorithms of search engine are classified. And we extend expression of queries by “keyword and ”, instead of keywords only. Second, a new ranking algorithm based on user feedback and semantic tags is
easy to bring the problem of topic excursion. Hits algorithm requires a number of pages as the basic-set for calculating and cannot be used in plain texts. This paper introduces a new algorithm: PK-TDC which makes use of the iterative idea of Hits. PK-TDC searches the authority pages and keywords on the topology of pages
Analyzing users' Web log data and extracting their interests of Web-watching behaviors are important and challenging research topics of Web usage mining. Users visit their favorite sites and sometimes search new sites by performing keyword search on search engines. Users' Web-watching behaviors can be regarded as a
Focused crawling is a mean for acquiring raw big data materials from the web. This paper proposes a focused crawler for discovering Arabic poetry resources based on the Apache Nutch crawler. The crawler identifies poetry relevant resources using an SVM classifier and a list of Arabic poetry related keywords. The
This paper presents an attempt to show the efficiency of some search engines in dealing with Arabic keywords. This can be achieved by comparing the number of retrieved pages, retrieving time, and stability (in both the number of retrieved pages and the order for each retrieved page) for each one of the selected 20
Search engines are one of the most powerful tools in the Web world today for data retrieval and exploration. Most search engines identify the key word in the sentence or phrase or list of words given by the user and starts mining the Web for the occurrence of keyword in the Web pages. Quite often searching for the key
. So this paper attempts to implement a commerce topic faced P2P search engine system for mobile devices using WAP protocol: MCTSE. MCTSE is built on the operating system of RedHat Linux AS3 Update4: it builds the topic characteristic keywords set using extendable iterative select keyword (EISK) algorithm, and based on
The use of Search Engine enables the information seeker to seek information from a wide range of categories. Cultural information is one of the unique categories among the classes of information searched by users. This is because, there exists a significant relationship between a cultural keyword and its' originating
-processing of Web search results have been extensively studied to help user effectively obtain useful information. This paper has basically three parts. First part is the review study on how the keyword is expanded through truncation or wildcards (which is a little known feature but one of the most powerful one) by using
Granular computing is an emerging technology. This paper summarizes its applications to the Web. A high frequent co-occurring ordered set of keywords is called a keyword set;it represents some concept in the given document set. These concepts forms a simplicial complex of concepts,which is regarded as a knowledge base
Current search engines have two problems, losing useful information and including useless information. These two problems are aroused by the keyword matching retrieval model, which is adopted by almost all search engines. We introduce the conception of category attribute of a word. According to the category attribute
, trained providers. To date the corresponding role of search engine technology use and efficacy has received relatively little attention, however. This study serves as an exploratory technology assessment that explains the application of keyword effectiveness indexing (KEI) analysis in estimating the ability of commercial
Analyzing users' Web log data and extracting their interests of Web-watching behaviors are important and challenging research topics of Web usage mining. Users visit their favorite sites and sometimes search new sites by performing keyword search on search engines. Users' Web-watching behaviors can be regarded as a
query-keywords are used as a basis for sentence extraction. Results obtained from experiments performed have shown that such a combined approach can provide very interesting similarity calculation and re-ranking measure. This can be used with reasonable efficiency to detect duplications on search results generated by
relational database of web pages. So there are many researches focusing on the search in these relational database with keywords, compared with these researches, our algorithms are mainly based on bags using the greedy algorithms and supporting the phrase recognition by utilizing multiple dictionaries. We make a comparison
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