Real Time Web Search Framework for Performing Efficient Retrieval of Data
With the rapidly growing amount of information on the internet, real-time system is one of the key strategies to cope with the information overload and to help users in finding highly relevant information. Real-time events and domain-specific information are important knowledge base references on th...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Zagreb, Faculty of organization and informatics
2021-01-01
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| Series: | Journal of Information and Organizational Sciences |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/383244 |
| _version_ | 1797206891654283264 |
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| author | Falah Al-akashi Diana Inkpen Inkpen |
| author_facet | Falah Al-akashi Diana Inkpen Inkpen |
| author_sort | Falah Al-akashi |
| collection | DOAJ |
| description | With the rapidly growing amount of information on the internet, real-time system is one of the key strategies to cope with the information overload and to help users in finding highly relevant information. Real-time events and domain-specific information are important knowledge base references on the Web that frequently accessed by millions of users. Real-time system is a vital to product and a technique must resolve the context of challenges to be more reliable, e.g. short data life-cycles, heterogeneous user interests, strict time constraints, and context-dependent article relevance. Since real-time data have only a short time to live, real-time models have to be continuously adapted, ensuring that real-time data are always up-to-date. The focal point of this manuscript is for designing a real-time web search approach that aggregates several web search algorithms at query time to tune search results for relevancy. We learn a context-aware delegation algorithm that allows choosing the best real-time algorithms for each query request. The evaluation showed that the proposed approach outperforms the traditional models, in which it allows us to adapt the specific properties of the considered real-time resources. In the experiments, we found that it is highly relevant for most recently searched queries, consistent in its performance, and resilient to the drawbacks faced by other algorithms. |
| first_indexed | 2024-04-24T09:14:13Z |
| format | Article |
| id | doaj.art-cf9b943605ca479fabb00ef2716e2e68 |
| institution | Directory Open Access Journal |
| issn | 1846-3312 1846-9418 |
| language | English |
| last_indexed | 2024-04-24T09:14:13Z |
| publishDate | 2021-01-01 |
| publisher | University of Zagreb, Faculty of organization and informatics |
| record_format | Article |
| series | Journal of Information and Organizational Sciences |
| spelling | doaj.art-cf9b943605ca479fabb00ef2716e2e682024-04-15T17:14:40ZengUniversity of Zagreb, Faculty of organization and informaticsJournal of Information and Organizational Sciences1846-33121846-94182021-01-0145128730810.31341/jios.45.1.13Real Time Web Search Framework for Performing Efficient Retrieval of DataFalah Al-akashi0Diana Inkpen Inkpen1Faculty of Engineering, University of Kufa, Najaf, IraqFaculty of Engineering, University of Ottawa, Ottawa, CanadaWith the rapidly growing amount of information on the internet, real-time system is one of the key strategies to cope with the information overload and to help users in finding highly relevant information. Real-time events and domain-specific information are important knowledge base references on the Web that frequently accessed by millions of users. Real-time system is a vital to product and a technique must resolve the context of challenges to be more reliable, e.g. short data life-cycles, heterogeneous user interests, strict time constraints, and context-dependent article relevance. Since real-time data have only a short time to live, real-time models have to be continuously adapted, ensuring that real-time data are always up-to-date. The focal point of this manuscript is for designing a real-time web search approach that aggregates several web search algorithms at query time to tune search results for relevancy. We learn a context-aware delegation algorithm that allows choosing the best real-time algorithms for each query request. The evaluation showed that the proposed approach outperforms the traditional models, in which it allows us to adapt the specific properties of the considered real-time resources. In the experiments, we found that it is highly relevant for most recently searched queries, consistent in its performance, and resilient to the drawbacks faced by other algorithms.https://hrcak.srce.hr/file/383244WikipediaResources CorrelationFederated SearchWeb MiningVector Space Model |
| spellingShingle | Falah Al-akashi Diana Inkpen Inkpen Real Time Web Search Framework for Performing Efficient Retrieval of Data Journal of Information and Organizational Sciences Wikipedia Resources Correlation Federated Search Web Mining Vector Space Model |
| title | Real Time Web Search Framework for Performing Efficient Retrieval of Data |
| title_full | Real Time Web Search Framework for Performing Efficient Retrieval of Data |
| title_fullStr | Real Time Web Search Framework for Performing Efficient Retrieval of Data |
| title_full_unstemmed | Real Time Web Search Framework for Performing Efficient Retrieval of Data |
| title_short | Real Time Web Search Framework for Performing Efficient Retrieval of Data |
| title_sort | real time web search framework for performing efficient retrieval of data |
| topic | Wikipedia Resources Correlation Federated Search Web Mining Vector Space Model |
| url | https://hrcak.srce.hr/file/383244 |
| work_keys_str_mv | AT falahalakashi realtimewebsearchframeworkforperformingefficientretrievalofdata AT dianainkpeninkpen realtimewebsearchframeworkforperformingefficientretrievalofdata |