What Shall I Do Next? Intention Mining for Flexible Process Enactment

International audienceBesides the benefits of flexible processes, practical implementations of process aware information systems have also revealed difficulties encountered by process participants during enactment. Several support and guidance solutions based on process mining have been proposed, but they lack a suitable semantics for human reasoning and decisions making as they mainly rely on low level activities. Applying design science, we created FlexPAISSeer, an intention mining oriented approach, with its component artifacts: 1) IntentMiner which discovers the intentional model of the executable process in an unsupervised manner; 2) In-tentRecommender which generates recommendations as intentions and confidence factors, based on the mined intentional process model and probabilistic calculus. The artifacts were evaluated in a case study with a Netherlands software company, using a Childcare system that allows flexible data-driven process enactment

Accurate and Efficient Search Prediction Using Fuzzy Matching and Outcome Feedback

While search engines have demonstrated improvement in both speed and accuracy, the response time to queries is prohibitively long for applications that require immediate and accurate responses to search queries. Examples include identification of multimedia resources related to the subject matter of a particular class, as it is in session. This paper begins with a survey of recommendation and prediction algorithms, each of which applies a different method to predict future search activity based on the search history of a user. To address the shortcomings identified in existing techniques, we draw inspiration from bioinformatics and latent semantic indexing to propose a novel predictive approach based on local alignment and feedback-based neighborhood refinement. We validate our proposed approach with tests on real-world search data. The results support our hypothesis that a majority of users exhibit search behavior that is predictable. Modeling this behavior enables our predictive search engine to bypass the common query-response model and proactively deliver a list of resources to the user