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- | [[http://esslli2009.labri.fr/|{{ :course:esslli09_logo.png|ESSLLI 2009 (Bordeaux)}}]] | + | These pages provide information, |
- | **Distributional Semantic Models: Theory and empirical results**\\ | + | ===== Schedules & handouts ===== |
- | //Advanced course at [[http:// | + | |
- | * [[course:schedule|Course schedule | + | * Advanced course on [[course:esslli2009: |
- | * [[course:material|Downloads & important links]] | + | * [[course: |
- | * [[course:bibliography|Suggested readings | + | * Introductory course on [[:course:esslli2018: |
+ | * Foundational course on [[:course:esslli2021: | ||
- | ===== Course description | + | ===== General information |
- | Distributional semantic models (DSMs) are based on the assumption that the meaning of a word can (at least to a certain extent) be inferred from its usage, i.e. its distribution in text. Therefore, these models dynamically build semantic representations – in the form of multi-dimensional vector spaces – through a statistical analysis of the contexts in which words occur. | + | * [[course: |
- | With their distributed vector-space representations, | + | * [[course: |
- | This course aims to equip participants with the necessary background knowledge for carrying out cutting-edge research in this area. In addition to teaching the mathematical foundations of DSMs and their applications in semantic analysis, we put particular emphasis on getting an intuitive grasp of the high-dimensional vector spaces, and on relating the computational models to fundamental issues of semantic theory. | ||
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- | **Lecturers: | ||
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- | Many thanks to all our participants for following this course and staying with us to the very end! We enjoyed the experience very much and hope to keep in touch with you. For this purpose, we're planning to set up a DSM mailing list, where you can exchange ideas, present your own DSM work, discuss possible DSM architectures, |