2/20/2023 0 Comments Tagspaces re arrange tag groupsWe cast web object classification problem as an optimization problem on a graph of objects and tags. In this paper, we explore the social tagging data to bridge this gap. Such ob- jects often suffer from a lack of easy-extractable features with semantic information, interconnections between each other, as well as training examples with category labels. The explosive growth of heterogeneous web objects, especially non-textual objects such as products, pictures, and videos, has made the prob- lem of web classification increasingly challenging. Automatically classi- fying web objects into manageable semantic categories has long been a fundamental preprocess for indexing, browsing, searching, and mining these objects. This paper studies web object classification problem with the novel exploration of social tags. The result of the experiment can be considered as evidence for the rich semantics of folksonomies, demonstrating that folksonomies used in the delicious bookmarking service can be used in the process of generating semantic metadata to annotate Web resources The experiment has been carried-out in two ways: automatically, by measuring the percentage of overlap between the folksonomy set and machine generated keywords set and subjectively, by asking a human indexer to evaluate the quality of the generated keywords from both systems. This paper reports on an experiment that we carried out to validate the assumption that folksonomies carry more semantic value than keywords extracted by machines. Manual techniques are expensive if they rely on skilled cataloguers, but a possible alternative is to make use of community produced annotations such as those collected in folksonomies. Semantic metadata, which describes the meaning of documents, can be produced either manually or else semi-automatically using information extraction techniques. Our conclusion will be relevant and beneficial for engineers and designers who aim to design and maintain a quality-protected folksonomy. We conclude our review with some of the interesting research topics, which need to be explored further. We have organized our paper by looking at the problem from four aspects namely selection of quality tags, tag management features provided by folksonomy applications, folksonomy cleaning and interoperability of tags across platforms. This is a survey paper, in which we present a brief survey of the research efforts intended to maintain a quality-protected folksonomy. It is required that quality of the folksonomy must remain consistently excellent and does not degrade with the passage of time. However, this freedom and liberty can degrade quality of the folksonomy. Apart from freedom, this system also reflects the collective intelligence of the crowd. We show that, in contrary to descriptive hashtags, stophashtags are characterized by high normalized subject (hashtag) frequency on irrelevant subject categories while normalized image frequency is also high.įolksonomy gives liberty to its users to freely assign chosen keywords as tags, and this is the main reason behind its popularity. In this study we call the latter category of Instagram hashtags as ‘stophashtags’, inspired from the term ‘stopwords’ which is used in the field of computational linguistics to refer to common and non-descriptive words found in almost every text document, and we provide a theoretical and empirical framework through which stophashtags can be identified. However, as we showed in a previous study, only 30 % of Instagram hashtags are related with the visual content of the accompanied photos while the remaining 70 % are either related with other meta-communicative functions of the photo owner/creator or they are simply noise and are used mainly to increase photo’s localization and searchability. Instagram could be considered as a tagged image dataset since it is reach in tags -known as hashtags- accompanying photos and, in addition, the tags are provided by photo owners/creators, thus, express in higher accuracy the meaning/message of the photos.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |