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        สล็อตหมุนฟรี ได้เงินจริง 2023

        The National Centre for Text Mining (NaCTeM) is the first publicly-funded text mining centre in the world. We provide text mining services in response to the requirements of the UK academic community.

        On our website, you can find pointers to sources of information about text mining such as links to

        • text mining services provided by NaCTeM
        • software tools, both those developed by the NaCTeM team and by other text mining groups
        • seminars, general events, conferences and workshops
        • tutorials and demonstrations
        • text mining publications
        Let us know if you would like to include any of the above in our website.

        What text mining can do for you

        Text mining offers a solution to the challenge of 'data deluge', information overload and information overlook. For more information, please see:

        NaCTeM has developed text mining services and service exemplars for the UK academic community. Our services are underpinned by a number of generic natural language processing tools:

        • TerMine is a Term Management System which identifies key phrases in text.
        • RobotAnalyst is a tool to minimise the human workload involved in the study identification phase of systematic reviews.
        • Thalia is a semantic search engine for Pubmed abstracts.
        • AcroMine is an acronym dictionary which can be used to find distinct expanded forms of acronyms from MEDLINE.
        • Kleio is an advanced information retrieval system providing knowledge enriched searching for biomedicine.
        • FACTA+ is a MEDLINE search engine for finding associations between biomedical concepts.
        • History of Medicine (HOM) – A semantic search system over historical medical archives
        • APLenty – An annotation tool for creating high-quality sequence labelling datasets using active and proactive learning
        • Paladin – A document classification annotation web application which supports active/proactive learning.
        • MEDIE uses semantic search to retrieve biomedical correlations from MEDLINE.
        • Info-PubMed uses a gene/protein dictionary and deep parsing to understand protein interactions [Firefox Required].