FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2127923309> ?p ?o ?g. }

• W2127923309 endingPage "112" @default.
• W2127923309 startingPage "87" @default.
• W2127923309 abstract "The advent of high‐speed Internet connections has revolutionized the way research is being carried out to obtain relevant information. Conversely, retrieving pertinent information from the copious resources available is not only difficult but also time consuming. In the recent years, tagging activity has been perceived as a potential source of knowledge on personal preferences, interests, targets, goals, and other attributes. Tags allow users to effectively annotate resources using keywords to personalize their recommendations and organize the resources for easy retrieval. However, the preference of users varies extremely resulting in tagging being counterproductive. These shortcomings reduce the application of the tagging system for filtering as well as retrieval of information. The tag recommendation system becomes useful by suggesting a set of relevant keywords to annotate the resources. This paper presents a review of the tag recommendation systems and the constraints that affects the available tag recommendation systems. Furthermore, we propose the use of spreading activation algorithm to study the role of constructed topic ontology for efficient tag recommendations. This approach is founded on the assumption that tags that are recommended to the user are predicted from the extracted keywords from the existing blogs and the topics in constructed topic ontology. We have also proposed a tag classification system, namely Correlation‐based Feature Selection–Hybrid Genetic Algorithm and classifier HGA‐SVM (support vector machine), and have compared the results with results produced by other existing feature selection methods. The results obtained from the experiments have been presented. WIREs Data Mining Knowl Discov 2015, 5:87–112. doi: 10.1002/widm.1149 This article is categorized under: Algorithmic Development > Web Mining Technologies > Classification Technologies > Computational Intelligence" @default.
• W2127923309 created "2016-06-24" @default.
• W2127923309 creator A5036334864 @default.
• W2127923309 creator A5053209487 @default.
• W2127923309 creator A5061645633 @default.
• W2127923309 creator A5078711341 @default.
• W2127923309 date "2015-04-09" @default.
• W2127923309 modified "2023-10-01" @default.
• W2127923309 title "Data mining-based tag recommendation system: an overview" @default.
• W2127923309 cites W121380867 @default.
• W2127923309 cites W1513751675 @default.
• W2127923309 cites W1530276735 @default.
• W2127923309 cites W1533841329 @default.
• W2127923309 cites W1541288193 @default.
• W2127923309 cites W1542664738 @default.
• W2127923309 cites W1549874165 @default.
• W2127923309 cites W1570159982 @default.
• W2127923309 cites W1595523455 @default.
• W2127923309 cites W1740848476 @default.
• W2127923309 cites W1964066675 @default.
• W2127923309 cites W1967386441 @default.
• W2127923309 cites W1971022461 @default.
• W2127923309 cites W1971272745 @default.
• W2127923309 cites W1973812756 @default.
• W2127923309 cites W1975153704 @default.
• W2127923309 cites W1978577143 @default.
• W2127923309 cites W1979248845 @default.
• W2127923309 cites W1981879326 @default.
• W2127923309 cites W1984681168 @default.
• W2127923309 cites W1985126569 @default.
• W2127923309 cites W1988470798 @default.
• W2127923309 cites W1989587422 @default.
• W2127923309 cites W1990843604 @default.
• W2127923309 cites W1998257453 @default.
• W2127923309 cites W1998374645 @default.
• W2127923309 cites W2007444087 @default.
• W2127923309 cites W2009119083 @default.
• W2127923309 cites W2015965379 @default.
• W2127923309 cites W2016257043 @default.
• W2127923309 cites W2020340745 @default.
• W2127923309 cites W2036055894 @default.
• W2127923309 cites W2036140203 @default.
• W2127923309 cites W2042281163 @default.
• W2127923309 cites W2056580848 @default.
• W2127923309 cites W2067634822 @default.
• W2127923309 cites W2070614186 @default.
• W2127923309 cites W2093394699 @default.
• W2127923309 cites W2102775690 @default.
• W2127923309 cites W2107473756 @default.
• W2127923309 cites W2109540001 @default.
• W2127923309 cites W2115805759 @default.
• W2127923309 cites W2116926073 @default.
• W2127923309 cites W2120721759 @default.
• W2127923309 cites W2122778642 @default.
• W2127923309 cites W2123733068 @default.
• W2127923309 cites W2127246734 @default.
• W2127923309 cites W2139420544 @default.
• W2127923309 cites W2146464078 @default.
• W2127923309 cites W2148698197 @default.
• W2127923309 cites W2156589869 @default.
• W2127923309 cites W2162788093 @default.
• W2127923309 cites W2292465834 @default.
• W2127923309 cites W2312386812 @default.
• W2127923309 cites W2321224343 @default.
• W2127923309 cites W2341865734 @default.
• W2127923309 cites W2396651124 @default.
• W2127923309 cites W281665770 @default.
• W2127923309 cites W2911401876 @default.
• W2127923309 cites W4205184193 @default.
• W2127923309 cites W4236122429 @default.
• W2127923309 cites W4249131251 @default.
• W2127923309 doi "https://doi.org/10.1002/widm.1149" @default.
• W2127923309 hasPublicationYear "2015" @default.
• W2127923309 type Work @default.
• W2127923309 sameAs 2127923309 @default.
• W2127923309 citedByCount "16" @default.
• W2127923309 countsByYear W21279233092016 @default.
• W2127923309 countsByYear W21279233092017 @default.
• W2127923309 countsByYear W21279233092018 @default.
• W2127923309 countsByYear W21279233092019 @default.
• W2127923309 countsByYear W21279233092020 @default.
• W2127923309 countsByYear W21279233092021 @default.
• W2127923309 countsByYear W21279233092023 @default.
• W2127923309 crossrefType "journal-article" @default.
• W2127923309 hasAuthorship W2127923309A5036334864 @default.
• W2127923309 hasAuthorship W2127923309A5053209487 @default.
• W2127923309 hasAuthorship W2127923309A5061645633 @default.
• W2127923309 hasAuthorship W2127923309A5078711341 @default.
• W2127923309 hasConcept C110875604 @default.
• W2127923309 hasConcept C111472728 @default.
• W2127923309 hasConcept C119857082 @default.
• W2127923309 hasConcept C12267149 @default.
• W2127923309 hasConcept C124101348 @default.
• W2127923309 hasConcept C136764020 @default.
• W2127923309 hasConcept C138885662 @default.
• W2127923309 hasConcept C148483581 @default.
• W2127923309 hasConcept C154945302 @default.
• W2127923309 hasConcept C23123220 @default.

• next