Аннотация
Tag recommender schemes suggest related tags for an untagged resource and better tag suggestions
to tagged resources. Tagging is very important if the user identifies the tag that is more precise
to use in searching interesting blogs. There is no clear information regarding the meaning of
each tag in a tagging process. An user can use various tags for the same content, and he can
also use new tags for an item in a blog. When the user selects tags, the resultant metadata may
comprise homonyms and synonyms. This may cause an improper relationship among items and
ineffective searches for topic information. The collaborative tag recommendation allows a set of
freely selected text keywords as tags assigned by users. These tags are imprecise, irrelevant, and
misleading because there is no control over the tag assignment. It does not follow any formal
guidelines to assist tag generation, and tags are assigned to resources based on the knowledge of
the users. This causes misspelled tags, multiple tags with the same meaning, bad word encoding,
and personalized words without common meaning. This problem leads to miscategorization of
items, irrelevant search results,wrong prediction, and their recommendations. Tag relevancy can be
judged only by a specific user. These aspects could provide new challenges and opportunities to its
tag recommendation problem. This paper reviews the challenges to meet the tag recommendation
problem. Abrief comparison between existing works is presented, which we can identify and point
out the novel research directions. The overall performance of our ontology-based recommender
systems is favorably compared to other systems in the literature.
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