Context-Sensitive Auto-Completion for Searching with Entities and Categories

Andreas Schmidt, Johannes Hoffart, Dragan Milchevski, Gerhard Weikum
2016 Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval - SIGIR '16  
When searching in a document collection by keywords, good auto-completion suggestions can be derived from query logs and corpus statistics. On the other hand, when querying documents which have automatically been linked to entities and semantic categories, auto-completion has not been investigated much. We have developed a semantic autocompletion system, where suggestions for entities and categories are computed in real-time from the context of already entered entities or categories and from
more » ... ity-level cooccurrence statistics for the underlying corpus. Given the huge size of the knowledge bases that underlie this setting, a challenge is to compute the best suggestions fast enough for interactive user experience. Our demonstration shows the effectiveness of our method, and its interactive usability.
doi:10.1145/2911451.2911461 dblp:conf/sigir/SchmidtHMW16 fatcat:f3czb5r34ng4dk5lmc5rtrsbze