Full-Text Search Engines for Databases

2009 ◽  
pp. 931-939
Author(s):  
László Kovács ◽  
Domonkos Tikk
Keyword(s):  
Information Retrieval ◽  
Full Text ◽  
Search Engines ◽  
Free Text ◽  
Text Search ◽  
Text Documents ◽  
Full Text Search ◽  
Textual Data ◽  
Efficient Information ◽  
Particular Solution

Current databases are able to store several Tbytes of free-text documents. The main purpose of a database from the user’s viewpoint is the efficient information retrieval. In the case of textual data, information retrieval mostly concerns the selection and the ranking of documents. We present here the particular solution of Oracle; there for making the full-text querying more efficient, a special engine was developed that performs the preparation of full-text queries and provides a set of language and semantic specific query operators.

scholarly journals Quantification of competitive value of documents

2009 ◽  
Vol 57 (5) ◽  
pp. 285-290
Author(s):  
Pavel Šimek ◽  
Jiří Vaněk ◽  
Jan Jarolímek
Keyword(s):  
Search Engine ◽  
Market Share ◽  
Full Text ◽  
Search Engines ◽  
Web Site ◽  
Optimization Techniques ◽  
Text Search ◽  
Full Text Search ◽  
Google Search ◽  
The Web

The majority of Internet users use the global network to search for different information using fulltext search engines such as Google, Yahoo!, or Seznam. The web presentation operators are trying, with the help of different optimization techniques, to get to the top places in the results of fulltext search engines. Right there is a great importance of Search Engine Optimization and Search Engine Marketing, because normal users usually try links only on the first few pages of the fulltext search engines results on certain keywords and in catalogs they use primarily hierarchically higher placed links in each category. Key to success is the application of optimization methods which deal with the issue of keywords, structure and quality of content, domain names, individual sites and quantity and reliability of backward links. The process is demanding, long-lasting and without a guaranteed outcome. A website operator without advanced analytical tools do not identify the contribution of individual documents from which the entire web site consists. If the web presentation operators want to have an overview of their documents and web site in global, it is appropriate to quantify these positions in a specific way, depending on specific key words. For this purpose serves the quantification of competitive value of documents, which consequently sets global competitive value of a web site. Quantification of competitive values is performed on a specific full-text search engine. For each full-text search engine can be and often are, different results. According to published reports of ClickZ agency or Market Share is according to the number of searches by English-speaking users most widely used Google search engine, which has a market share of more than 80%. The whole procedure of quantification of competitive values is common, however, the initial step which is the analysis of keywords depends on a choice of the fulltext search engine.

Research and Improvement on Content-Based Web Search Engine

2012 ◽  
Vol 532-533 ◽  
pp. 1282-1286
Author(s):  
Zhi Chao Lin ◽  
Lei Sun ◽  
Xiao Liu
Keyword(s):  
Information Retrieval ◽  
Search Engine ◽  
Full Text ◽  
Search Engines ◽  
Query Expansion ◽  
Web Search ◽  
Text Search ◽  
Web Search Engine ◽  
Query Word ◽  
The Web

There is a lot of information contained in the World Wide Web. It has become a research focus to obtain the required related resources quickly and accurately from the web through the content-based search engines. Most current tools of full text web search engine, such as Lucene which is a widely used open source retrieval library in information retrieval field, are purely keyword based. This may not sufficient for users to retrieve in the web. In this paper, we employ a method to overcome the limitations of current full text search engines in represent of Lucene. We propose a Query Expansion and Information Retrieval approach which can help users to acquire more accurate contents from the web. The Query Expansion component finds expanded candidate words of the query word through WordNet which contains synonyms in several different senses; In the Information Retrieval component, the query word and its candidate words are used together as the input of the search module to get the result items. Furthermore, we can put the result items into different classes based on the expansion. Some experiments and the results are described in the late part of this paper.

Full-Text Search Engines for Databases

2011 ◽  
pp. 654-660
Author(s):  
László Kovács ◽  
Domonkos Tikk
Keyword(s):  
Information Retrieval ◽  
Language Processing ◽  
Full Text ◽  
Database Management ◽  
Traditional Approach ◽  
Database Management Systems ◽  
Management Systems ◽  
Exact Matching ◽  
Text Search ◽  
Full Text Search

Current databases are able to store several Tbytes of free-text documents. The main purpose of a database from the user’s viewpoint is the efficient information retrieval. In the case of textual data, information retrieval mostly concerns the selection and the ranking of documents. The selection criteria can contain elements that apply to the content or the grammar of the language. In the traditional database management systems (DBMS), text manipulation is restricted to the usual string manipulation facilities, i.e. the exact matching of substrings. Although the new SQL1999 standard enables the usage of more powerful regular expressions, this traditional approach has some major drawbacks. The traditional string-level operations are very costly for large documents as they work without task-oriented index structures. The required full-text management operations belong to text mining, an interdisciplinary field of natural language processing and data mining. As the traditional DBMS engine is inefficient for these operations, database management systems are usually extended with a special full-text search (FTS) engine module. We present here the particular solution of Oracle; there for making the full-text querying more efficient, a special engine was developed that performs the preparation of full-text queries and provides a set of language and semantic specific query operators.

The information retrieval anthology 2021

2021 ◽  
Vol 55 (1) ◽  
pp. 1-18
Author(s):  
Martin Potthast ◽  
Benno Stein ◽  
Matthias Hagen
Keyword(s):  
Information Retrieval ◽  
Search Engine ◽  
Full Text ◽  
Use Cases ◽  
Text Search ◽  
Full Text Search ◽  
Comprehensive Collection ◽  
To Come

The Information Retrieval Anthology, IR Anthology for short, is an endeavor to create a comprehensive collection of metadata and full texts of IR-related publications. We report on its first release, the use cases it can serve, as well as the challenges lying ahead to develop it towards a resource that serves the IR community for years to come. The IR Anthology's metadata browser and full text search engine are available at IR.webis.de.

When 57,300,000 Full Text Search Results Are Just Too Many

2014 ◽  
Author(s):  
Pat Case
Keyword(s):  
Full Text ◽  
Search Engines ◽  
End Users ◽  
End User ◽  
New Paradigm ◽  
Text Search ◽  
Full Text Search ◽  
Search Results ◽  
Impressive Result ◽  
The Web

The Web changed the paradigm for full-text search. Searching Google for search engines returns 57,300,000 results at this writing, an impressive result set. Web search engines favor simple searches, speed, and relevance ranking. The end user most often finds a wanted result or two within the first page of search results. This new paradigm is less useful in searching collections of homogeneous data and documents than it is for searching the web. When searching collections end users may need to review everything in the collection on a topic, or may want a clean result set of only those 6 high-quality results, or may need to confirm that there are no wanted results because finding no results within a collection sometimes answers a question about a topic or collection. To accomplish these tasks, end users may need more end user functionality to return small, manageable result sets. The W3C XQuery and XPath Full Text Recommendation (XQFT) offers extensive end user functionality, restoring the end user control that librarians and expert searches enjoyed before the Web. XQFT offers more end user functionality and control than any other full-text search standard ever: more match options, more logical operators, more proximity operators, more ways to return a manageable result set. XQFT searches are also completely composable with XQuery string, number, date, and node queries, bringing the power of full-text search and database querying together for the first time. XQFT searches run directly against XML, enabling searches on any elements or attributes. XQFT implementations are standard-driven, based on shared semantics and syntax. A search in any implementation is portable and may be used in other implementations.

GPU Computation for Online Realtime Multi-Pattern Matching

2013 ◽  
Vol 284-287 ◽  
pp. 3428-3432 ◽  
Author(s):  
Yu Hsiu Huang ◽  
Richard Chun Hung Lin ◽  
Ying Chih Lin ◽  
Cheng Yi Lin
Keyword(s):  
Parallel Computation ◽  
Pattern Matching ◽  
Full Text ◽  
Network Performance ◽  
Text Search ◽  
Full Text Search ◽  
Network Intrusion ◽  
Speed Up ◽  
Set Up ◽  
Gpu Implementation

Most applications of traditional full-text search, e.g., webpage search, are offline which exploit text search engine to preview the texts and set up related index. However, applications of online realtime full-text search, e.g., network Intrusion detection and prevention systems (IDPS) are too hard to implementation by using commodity hardware. They are expensive and inflexible for more and more occurrences of new virus patterns and the text cannot be previewed and the search must be complete realtime online. Additionally, IDPS needs multi-pattern matching, and then malicious packets can be removed immediately from normal ones without degrading the network performance. Considering the problem of realtime multi-pattern matching, we implement two sequential algorithms, Wu-Manber and Aho-Corasick, respectively over GPU parallel computation platform. Both pattern matching algorithms are quite suitable for the cases with a large amount of patterns. In addition, they are also easier extendable over GPU parallel computation platform to satisfy realtime requirement. Our experimental results show that the throughput of GPU implementation is about five to seven times faster than CPU. Therefore, pattern matching over GPU offers an attractive solution of IDPS to speed up malicious packets detection among the normal traffic by considering the lower cost, easy expansion and better performance.

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