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X-WR-CALDESC:Events for Semantic Web Company
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DTSTART:20210101T000000
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DTSTART;TZID=UTC:20220713T150000
DTEND;TZID=UTC:20220713T160000
DTSTAMP:20260430T141621
CREATED:20230213T125022Z
LAST-MODIFIED:20230213T125022Z
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SUMMARY:Webinar: Semantic Web enabled Machine Learning
DESCRIPTION:Semantic Web enabled Machine Learning\nPresenter: Anna Breit\, Victor Mireles \nWe present an overview of the use of Semantic Web technologies in Machine Learning workflows. We will start by a general overview of the different steps in the application of Machine Learning techniques to real world cases. \nAfterwards\, the viewers will be treated to a series of examples of the successful use of Knowledge Graphs in several of these steps. These examples will show how Semantic Web Technologies can improve machine learning solutions in the fields of image processing\, biomedical data analysis\, and natural language processing. This will help them reflect on their existing machine learning pipelines\, and on ways to combine into them any knowledge that they have organized into graphs.
URL:https://semantic-web.com/research-event/webinar-semantic-web-enabled-machine-learning/
ATTACH;FMTTYPE=image/png:https://semantic-web.com/wp-content/uploads/webinar-semantic-web-enabled-machine-learning-6.png
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BEGIN:VEVENT
DTSTART;TZID=UTC:20210907T043000
DTEND;TZID=UTC:20210907T053000
DTSTAMP:20260430T141621
CREATED:20230213T112307Z
LAST-MODIFIED:20230213T112307Z
UID:144956-1630989000-1630992600@semantic-web.com
SUMMARY:Talk @Semantics 2021
DESCRIPTION:Annotating Entities with Fine-Grained Types in Austrian Court Decisions\nSpeaker: Artem Revenko \nThe usage of Named Entity Recognition tools on domain specific corpora is often hampered by insufficient training data. We investigate an approach to produce fine-grained named entity annotations from a small training dataset to later apply it on a large corpus of Austrian court decisions. We apply general purpose Named Entity Recognition model to produce annotations of common coarse-grained types. Next\, a small sample of these annotations are manually annotated by domain experts to produce initial fine-grained training datset.
URL:https://semantic-web.com/research-event/talk-semantic/
ATTACH;FMTTYPE=image/png:https://semantic-web.com/wp-content/uploads/talk-semantics-20211.png
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BEGIN:VEVENT
DTSTART;TZID=UTC:20210421T030000
DTEND;TZID=UTC:20210421T170000
DTSTAMP:20260430T141621
CREATED:20230206T150341Z
LAST-MODIFIED:20230206T150341Z
UID:144954-1618974000-1619024400@semantic-web.com
SUMMARY:Talk @EACL 2021
DESCRIPTION:WiC-TSV: An Evaluation Benchmark for Target Sense Verification of Words in Context\nPresenter: Anna Breit \nAbstract: We present WiC-TSV\, a new multi-domain evaluation benchmark for Word Sense Disambiguation. More specifically\, we introduce a framework for Target Sense Verification of Words in Context which grounds its uniqueness in the formulation as binary classification task thus being independent of external sense inventories\, and the coverage of various domains. This makes the dataset highly flexible for the evaluation of a diverse set of models and systems in and across domains. WiC-TSV provides three different evaluation settings\, depending on the input signals provided to the model. We set baseline performance on the dataset using state-of-the-art language models. Experimental results show that even though these models can perform decently on the task\, there remains a gap between machine and human performance\, especially in out-of-domain settings. WiC-TSV data is available at https://competitions.codalab.org/competitions/23683.
URL:https://semantic-web.com/research-event/talk-eacl-2021/
ATTACH;FMTTYPE=image/png:https://semantic-web.com/wp-content/uploads/talk-eacl-2021-2.png
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BEGIN:VEVENT
DTSTART;TZID=UTC:20210224T114500
DTEND;TZID=UTC:20210224T123000
DTSTAMP:20260430T141621
CREATED:20230206T144444Z
LAST-MODIFIED:20230206T144444Z
UID:144953-1614167100-1614169800@semantic-web.com
SUMMARY:Invited Talk @Winter School of KnowGraphs
DESCRIPTION:Application talk: PoolParty Semantic Suite and Knowledge Graph Management\nPresenter: Martin Kaltenböck and Artem Revenko \nAbstract: The amount of structured\, semi-structured and unstructured data in organisations is growing heavily and data and information is often stored in silos inside of department solutions\, but organisations are interested in unified 360 degree views on their data and information to be able to make precise and sustainable decisions. Enterprise Knowledge Graphs can solve this problem by integrating data and information from heterogeneous sources in different formats by mapping it to one or more central knowledge models and linking it to each other in the form of a Knowledge Graph. This talk will provide a short introduction into the problem statement and why and how Knowledge Graphs can help\, furthermore it gives a short introduction into PoolParty Semantic Suite\, a Semantic Middleware for powerful Knowledge Graph applications and finally it will provide an overview of the most important use cases that Enterprise Knowledge Graphs can solve.
URL:https://semantic-web.com/research-event/application-talk-poolparty-semantic-suite-and-knowledge-graph-management/
ATTACH;FMTTYPE=image/png:https://semantic-web.com/wp-content/uploads/invited-talk-winter-school-of-knowgraphs.png
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BEGIN:VEVENT
DTSTART;TZID=UTC:20210108T080000
DTEND;TZID=UTC:20210108T121000
DTSTAMP:20260430T141621
CREATED:20230202T132949Z
LAST-MODIFIED:20230202T132949Z
UID:144952-1610092800-1610107800@semantic-web.com
SUMMARY:Presentation @SemDeep-6
DESCRIPTION:Introduction to the Target Sense Verification for Word in Context (WiC-TSV) Challenge\nPresenter: Anna Breit \nhttps://competitions.codalab.org/competitions/23683
URL:https://semantic-web.com/research-event/presentation-semdeep-6/
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