Abstract
Access to knowledge about user goals represents a critical component for realizing the vision of intelligent agents acting
upon user intent on the web. Yet, the manual acquisition of knowledge about user goals is costly and often infeasible. Ina departure from existing approaches, this paper proposes Goal Mining as a novel perspective for knowledge acquisition. Theresearch presented in this chapter makes the following contributions: (a) it presents Goal Mining as an emerging field of research and a corresponding automatic method for the acquisition of user goals from web corpora,in the case of this paper search query logs (b) it provides insights into the nature and some characteristics of these goalsand (c) it shows that the goals acquired from query logs exhibit traits of a long tail distribution, thereby providing accessto a broad range of user goals. Our results suggest that search query logs represent a viable, yet largely untapped resource for acquiring knowledge about explicit user goals.
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