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Abstract: Online photo services such as Flickr and Zooomr allow users to share their photos with family, friends, and the online community at large. An important facet of these services is that users manually annotate their photos using so called tags, which describe the contents of the photo or provide additional contextual and semantical information. In this paper we investigate how we can assist users in the tagging phase. The contribution of our research is twofold. We analyse a representative snapshot of Flickr and present the results by means of a tag characterisation focussing on how users tags photos and what information is contained in the tagging. Based on this analysis, we present and evaluate tag recommendation strategies to support the user in the photo annotation task by recommending a set of tags that can be added to the photo. The results of the empirical evaluation show that we can effectively recommend relevant tags for a variety of photos with different levels of exhaustiveness of original tagging.

Abstract: A method and apparatus are provided for retrieving documents from a collection of documents based on information other than the contents of a desired document. The collection of documents, which may be a hypertext system or documents available via the World Wide Web, is indexed. In one embodiment, an indexing process of a search engine receives one or more specifications that identify documents, or document locations, and non-content information such as a tag word or code word. The indexing process searches the index to identify all documents in the index that match one or more of the specifications. If a match is found, the tag word is added to the index, and information about the matching document is stored in the index in association with the tag word. A search query is submitted to the search engine. The search query is automatically modified to add a reference to the tag word, such as a query term that will exclude any index entry for a document associated with the tag word. The search is executed against the index, and a set of search results is generated. Accordingly, the search results automatically exclude all documents associated with the tag word. These techniques may be used, for example, to implement a Web search service that produces more accurate search results or that prevents certain documents, such as pornographic materials, from appearing in search results.

Abstract: Collaborative tagging services (folksonomies) have been among the stars of the Web 2.0 era. They allow their users to label diverse resources with freely chosen keywords (tags). Our studies of two real-world folksonomies unveil that individual users develop highly personalized vocabularies of tags. While these meet individual needs and preferences, the considerable differences between personal tag vocabularies (personomies) impede services such as social search or customized tag recommendation. In this paper, we introduce a novel user-centric tag model that allows us to derive mappings between personal tag vocabularies and the corresponding folksonomies. Using these mappings, we can infer the meaning of user-assigned tags and can predict choices of tags a user may want to assign to new items. Furthermore, our translational approach helps in reducing common problems related to tag ambiguity, synonymous tags, or multilingualism. We evaluate the applicability of our method in tag recommendation and tag-based social search. Extensive experiments show that our translational model improves the prediction accuracy in both scenarios.

Abstract: We evaluate the effectiveness of using the HTML META tag to improve retrieval of World Wide Web documents through Internet search engines. Twenty documents were created in five subject areas: agricultural trade, farm business statistics, poultry statistics, vegetable statistics, and cotton statistics. Four pages were created in each subject area: one with no META tags, one with a META tag using the keywords attribute, one with a META tag using the description attribute, and one with META tags using both the keywords and description attributes. Searches were performed in AltaVista and Infoseek to find terms common to all pages as well as for each keyword term contained in the META tag. Analysis of the searches suggests that the use of the keywords attribute in a META tag substantially improves accessibility while use of the description attribute alone does not. These results suggest that HTML document authors should consider using keywords attribute META tags. We also suggest that more search engines index the META tag to improve resource discovery.