Ayush Singhal and Jaideep Srivastava, University of Minnesota, USA

Tagging documents with relevant and comprehensive keywords offer invaluable assistance to the readers to quickly overview any document. With the ever increasing volume and variety of the documents published on the internet, the interest in developing newer and successful techniques for annotating (tagging) documents is also increasing. However, an interesting challenge in document tagging occurs when the full content of the document is not readily accessible. In such a scenario, techniques which use “short text”, e.g., a document title, a news article headline, to annotate the entire article are particularly useful. In this paper, we pro- pose a novel approach to automatically tag documents with relevant tags or key-phrases using only “short text” information from the documents. We employ crowd-sourced knowledge from Wikipedia, Dbpedia, Freebase, Yago and similar open source knowledge bases to generate semantically relevant tags for the document. Using the intelligence from the open web, we prune out tags that create ambiguity in or “topic drift” from the main topic of our query document. We have used real world dataset from a corpus of research articles to annotate 50 research articles. As a baseline, we used the full text information from the document to generate tags. The proposed and the baseline approach were compared using the author assigned keywords for the documents as the ground truth information. We found that the tags generated using proposed approach are better than using the baseline in terms of overlap with the ground truth tags measured via Jaccard index (0.058 vs. 0.044). In terms of computational efficiency, the proposed approach is at least 3 times faster than the baseline approach. Finally, we qualitatively analyse the quality of the predicted tags for a few samples in the test corpus. The evaluation shows the effectiveness of the proposed approach both in terms of quality of tags generated and the computational time.

Semantic annotation, open source knowledge, wisdom of crowds, tagging.