NEER: An Unsupervised Method for Named Entity Evolution Recognition
Nina Tahmasebi | Gerhard Gossen | Nattiya Kanhabua | Helge Holzmann | Thomas Risse
Proceedings of COLING 2012
fokas: Formerly Known As – A Search Engine Incorporating Named Entity Evolution
Helge Holzmann | Gerhard Gossen | Nina Tahmasebi
Proceedings of COLING 2012: Demonstration Papers
Classifying Action Items for Semantic Email
Simon Scerri | Gerhard Gossen | Brian Davis | Siegfried Handschuh
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)
Email can be considered as a virtual working environment in which users are constantly struggling to manage the vast amount of exchanged data. Although most of this data belongs to well-defined workflows, these are implicit and largely unsupported by existing email clients. Semanta provides this support by enabling Semantic Email ― email enhanced with machine-processable metadata about specific types of email Action Items (e.g. Task Assignment, Meeting Proposal). In the larger picture, these items form part of ad-hoc workflows (e.g. Task Delegation, Meeting Scheduling). Semanta is faced with a knowledge-acquisition bottleneck, as users cannot be expected to annotate each action item, and their automatic recognition proves difficult. This paper focuses on applying computationally treatable aspects of speech act theory for the classification of email action items. A rule-based classification model is employed, based on the presence or form of a number of linguistic features. The technologys evaluation suggests that whereas full automation is not feasible, the results are good enough to be presented as suggestions for the user to review. In addition the rule-based system will bootstrap a machine learning system that is currently in development, to generate the initial training sets which are then improved through the users reviewing.
- Nina Tahmasebi 2
- Helge Holzmann 2
- Simon Scerri 1
- Brian Davis 1
- Siegfried Handschuh 1
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