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  2. Semantic gap - Wikipedia

    en.wikipedia.org/wiki/Semantic_gap

    Consequently, any mapping from real world applications into computer applications requires a certain amount of technical background knowledge by the user, where the semantic gap manifests itself. It is a fundamental task of software engineering to close the gap between application specific knowledge and technically doable formalization. For ...

  3. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    The dataset is labeled with semantic labels for 32 semantic classes. over 700 images Images Object recognition and classification 2008 [56] [57] [58] Gabriel J. Brostow, Jamie Shotton, Julien Fauqueur, Roberto Cipolla RailSem19 RailSem19 is a dataset for understanding scenes for vision systems on railways. The dataset is labeled semanticly and ...

  4. Semantic Scholar - Wikipedia

    en.wikipedia.org/wiki/Semantic_Scholar

    Semantic Scholar is a research tool for scientific literature. It is developed at the Allen Institute for AI and was publicly released in November 2015. [2] Semantic Scholar uses modern techniques in natural language processing to support the research process, for example by providing automatically generated summaries of scholarly papers. [3]

  5. Computational semantics - Wikipedia

    en.wikipedia.org/wiki/Computational_semantics

    Computational semantics is the study of how to automate the process of constructing and reasoning with meaning representations of natural language expressions. [1] It consequently plays an important role in natural-language processing and computational linguistics.

  6. Multimedia information retrieval - Wikipedia

    en.wikipedia.org/wiki/Multimedia_Information...

    Multimedia information retrieval (MMIR or MIR) is a research discipline of computer science that aims at extracting semantic information from multimedia data sources. [1] [failed verification] Data sources include directly perceivable media such as audio, image and video, indirectly perceivable sources such as text, semantic descriptions, [2] biosignals as well as not perceivable sources such ...

  7. Topic model - Wikipedia

    en.wikipedia.org/wiki/Topic_model

    The author-topic model by Rosen-Zvi et al. [13] models the topics associated with authors of documents to improve the topic detection for documents with authorship information. HLTA was applied to a collection of recent research papers published at major AI and Machine Learning venues. The resulting model is called The AI Tree.

  8. Computer Science Ontology - Wikipedia

    en.wikipedia.org/wiki/Computer_Science_Ontology

    The Computer Science Ontology (CSO) is an automatically generated taxonomy of research topics in the field of Computer Science. [ 1 ] [ 2 ] It was produced by the Open University in collaboration with Springer Nature by running an information extraction system over a large corpus of scientific articles. [ 3 ]

  9. Knowledge representation and reasoning - Wikipedia

    en.wikipedia.org/wiki/Knowledge_representation...

    One of the most active areas of knowledge representation research is the Semantic Web. [citation needed] The Semantic Web seeks to add a layer of semantics (meaning) on top of the current Internet. Rather than indexing web sites and pages via keywords, the Semantic Web creates large ontologies of concepts. Searching for a concept will be more ...

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