Web-based Information Retrieval System Research Articles

The New Version of the ANDDigest Tool with Improved AI-Based Short Names Recognition

The body of scientific literature continues to grow annually. Over 1.5 million abstracts of biomedical publications were added to the PubMed database in 2021. Therefore, developing cognitive systems that provide a specialized search for information in scientific publications based on subject area ontology and modern artificial intelligence methods is urgently needed. We previously developed a web-based information retrieval system, ANDDigest, designed to search and analyze information in the PubMed database using a customized domain ontology. This paper presents an improved ANDDigest version that uses fine-tuned PubMedBERT classifiers to enhance the quality of short name recognition for molecular-genetics entities in PubMed abstracts on eight biological object types: cell components, diseases, side effects, genes, proteins, pathways, drugs, and metabolites. This approach increased average short name recognition accuracy by 13%.

A Firefly Algorithm-Based Approach for Web Query Reformulation

A major difficulty in using a web-based information retrieval system is the choice of terms to be used for expressing and processing a query. The user has to examine a lot of data to find the necessary documents or information. The problem that often appears in this situation is that the query is incorrect and does not express those needs. Researchers have come up with various solutions to overcome this problem among them the use of query reformulation. This paper presents an approach called FA-QR based on this technique using the Firefly metaheuristic. This algorithm was applied to frequent itemsets generated by frequent- pattern growth (FP Growth). The algorithmic solution allowed the user to select the best path among all the possible solutions for the initial query. Experimentally, the results demonstrated that our proposed approaches achieved a significant improvement over other different methods on TREC and FIRE datasets.

Incremental Refinement of Page Ranking of Web Pages

Web-based information retrieval systems called search engines have made things easy for information seekers, but still do not provide guarantees about the relevance of the information provided to the users. Information retrieval systems provide the information to the user based on certain retrieval criteria. Due to the large size of the WWW, it is very common that a large number of documents get identified related to a particular domain. Therefore, to help users towards finding the best matching documents, a ranking mechanism is employed by the search engine. In this article, an improved architecture for an information retrieval system is proposed. The proposed system makes a query log for each user query and stores the results retrieved to the user for that query. The system also provides relevant results by analyzing the content of the pages retrieved for the user query.

Towards an Arabic Web-based Information Retrieval System (ARABIRS): Stemming to Indexing

Arabic, the mother tongue of over 300 million people around the world, is known as one of the most difficult languages in Automatic Natural Language processing (NLP) in general and information retrieval in particular. Hence, Arabic cannot trust any web information retrieval system as reliable and relevant as Google search engine. In this context, we dared to focus all our researches to implement an Arabic web-based information retrieval system entitled ARABIRS (ARABic Information Retrieval System). Therefore, to launch such a process so long and hard, we will start with Indexing as one of the crucial steps of the system. General Terms Natural Languages Processing , Arabic Language Processing, Information Retrieval.

A Model of Vertical Crawler Based on Hidden Markov Chain

The large size and the dynamic nature of the Web make it necessary to continually maintain Web based information retrieval systems. In order to get more objects by visiting few irrelevant web pages, the web crawler usually takes the heuristic searching strategy that ranks urls by their importance and preferentially visits the more important web pages. While some systems rely on crawlers that exhaustively crawl the Web, others incorporate “focus” within their crawlers to harvest application or topic-specific collections. In this paper, using the Hidden Markov Model(HMM) learning ability to solve the problem of the theme of the crawler drift, has obtained the certain effect.

Novel Approaches for Integrating MART1 Clustering Based Pre-Fetching Technique with Web Caching

Web caching and Web pre-fetching are two important techniques for improving the performance of Web based information retrieval system. These two techniques would complement each other, since Web caching provides temporal locality whereas Web pre-fetching provides spatial locality of Web objects. However, if the web caching and pre-fetching are integrated inefficiently, this might cause increasing the network traffic as well as the Web server load. Conventional policies are most suitable only for memory caching since it involves fixed page size. But when one deals with web caching which involves pages of different size. Hence one need an efficient algorithm that works better in web cache environment. Moreover conventional replacement policies are not suitable in clustering based pre-fetching environment since multiple objects were pre-fetched. Hence, it cannot be handled by conventional algorithms. Therefore, care must be taken while integrating web caching with web pre-fetching technique in order to overcome these limitations. In this paper, novel algorithms have been proposed for integrating web caching with clustering based pre-fetching technique. Here Modified ART1 has been used for clustering based pre-fetching technique. The proposed algorithm outperforms the traditional algorithms in terms of hit rate and number of objects to be pre-fetched. Hence saves bandwidth.

PERSONALIZING THE SOURCE SELECTION AND THE RESULT MERGING PROCESS

The World Wide Web knows an incessant and very fast development. Currently, finding useful information on the Web is a time consuming process. In this paper, we present PIRS a personalized Information Retrieval System in a distributed environment. Most prior research in distributed information access focused on selecting and merging information that has the most relevant content according to the query but ignored the user's specific needs. The underlying idea is that different users have different backgrounds, goals and interests when seeking information and thus, the same query may cover different specific information needs according to who emitted it. However, with the ever expanding Web, users are faced with a huge number of information resources. Consequently, such query-based information access strategies lead to inaccurate query results. PIRS extends the state of the art in a Web-based information retrieval system in distributed environment. First, it develops models for representing both user and information source using feature based profiles. Second, PIRS expands a user query according to his profile. Third, it develops algorithms for source selection and results merging that personalize the computation of the relevance score of a document in response to the user's query. PIRS has been experimented with several known information source. The experimental results obtained show the effectiveness of our approach.

자동화된 통합 프레임워크를 위한 시맨틱 웹 기반의 정보 검색 시스템

자동화된 통합 프레임워크를 위한 시맨틱 웹 기반의 정보 검색 시스템

Design and Development of a Cross Search Engine for Multiple Heterogeneous Databases Using UML and Design Patterns

As the popularity and complexity of Internet search engines increase, the design, development and maintenance of large, complex web-based Information Retrieval (WIR) systems become a challenge. The difficulty of designing a WIR system is compounded by information overload triggered from various different information sources. From a standpoint of the search engine users, it is more usable for the WIR to provide a single search point to multiple databases. To tackle this issue, we present the design and implementation of a cross-search component for the CS-Engine (Cross-Search Engine). The CS-Engine allows the user to search heterogeneous, multiple databases with one command. The CS-Engine is also distinguished from meta-search engines in that the CS-Engine does not need to trigger other search engines and translate a query for other search engines. Our performance benchmark tests show that the CS-Engine is scalable and usable. We also compare CS-engine with other search engines such as Google and AltaVista. The CS-Engine was developed with UML and design patterns including: (1) use case diagram, (2) class diagram, (3) package diagram, (4) interaction diagram, (5) Factory pattern, and (6) Strategy patterns. We conclude our paper with technical lessons learned as well as organizational issues encountered during the development phase.

Design considerations in instrumenting and monitoring web-based information retrieval systems

The Internet Web environment opens up extraordinary opportunities for user access to information. Techniques for monitoring users and systems and for evaluating system design and performance have not kept pace with Web development. This article reviews concepts of Web operations (including browsers, clients, information retrieval applications, servers, and data communications systems) with specific attention given to how monitoring should take place and how privacy can be protected. It examines monitoring needs of users, systems designers, managers, and customer support staff and outlines measures of workload, capacity, and performance for hardware, software, and data communications systems. Finally, the article proposes a client-server design for monitoring, which involves creation of a series of server and client systems to obtain and process transaction and computer performance information. These systems include: A Log Server, which captures all levels of transactions and packets on the network; a Monitor Server, which synthesizes the log and packet data; an Assistance Server, which processes requests for information and help from the Web Server in real time; and an Accounting Server, which authenticates user access to the system. A special System Administrator Client is proposed to control the monitoring system, as is a System Information Client to receive real-time and on-demand reports of system activity. © 1998 John Wiley & Sons, Inc.