- From: Paola Di Maio <paoladimaio10@gmail.com>
- Date: Wed, 21 Aug 2019 13:16:59 +0800
- To: W3C AIKR CG <public-aikr@w3.org>, Gannon Dick <gannon_dick@yahoo.com>
- Message-ID: <CAMXe=Soxf-3gjAm7dRGyz-=VTxRhsv4qpNEoK5sy-BJGU=ch-w@mail.gmail.com>
Gannon, thanks for reply forwarded to list ---------- Forwarded message --------- From: Gannon Dick <gannon_dick@yahoo.com> Date: Wed, Aug 21, 2019 at 2:31 AM Subject: Fw: AI tools for scientific literature exploration and cognitive discovery and the use of semantic technologies therein To: paoladimaio10@googlemail.com <paoladimaio10@googlemail.com> Hi Paola, He's talking about your stuff "A plethora of tools is now available, yet it is unclear whether in all of these semantic web technologies can be or are used." My thoughts ... The data base long pre-dates semantic methods. The origin of PubMed <https://www.ncbi.nlm.nih.gov/pmc/> was 1921 IIRC. The articles are 100% peer reviewed. What this excludes from searches is scientific priority disputes. Semantic search methods include these results and thereby increase uncertainty but without any increase in entropy which I can justify ... which explains why using Kelvin's tide tables from 1900 is a real bad idea. The fact they are hard to read having been copied a million times is just a gatekeeper bonus. In Medicine and Molecular Biology there are some gains to be made by looking backward but the reason is often a low incidence of a rare syndrome. This is a much different task than Machine Learning which can only identify good candidates for further study. --Gannon ----- Forwarded Message ----- *From:* ProjectParadigm-ICT-Program <metadataportals@yahoo.com> *To:* Public-lod Public <public-lod@w3.org>; W3C AIKR CG <public-aikr@w3.org>; Ontolog-forum <ontolog-forum@googlegroups.com>; Semantic-web < semantic-web@w3.org>; public-philoweb@w3.o <public-philoweb@w3.org>; W3c Semweb HCLS <public-semweb-lifesci@w3.org> *Sent:* Tuesday, August 20, 2019, 12:25:00 PM CDT *Subject:* AI tools for scientific literature exploration and cognitive discovery and the use of semantic technologies therein As the amount of scientific literature, the body of both peer reviewed and open publishing literature seems to grow exponentially, the need to use search tools that employ AI to rapidly weed out less relevant material and find material that meets narrow search criteria will grow. A plethora of tools is now available, yet it is unclear whether in all of these semantic web technologies can be or are used. AI used for scientific literature exploration and for cognitive discovery could benefit from the use of semantic web technologies if the knowledge representation tools used by AI would incorporate such. The W3 AIKR CG is looking into this and related issues. General literature exploration and cognitive discovery stand to gain from semantic web enabled AI-KR, and this might be just the breakthrough application for semantic web technologies. Has any research been done on the use of AI enabled scientific literature exploration in selected domains (disciplines), comparative studies on the use of semantic web technologies and other technologies, and developed benchmarks or metrics for measuring AI enabled literature exploration tools and semantic web technologies in such? Milton Ponson GSM: +297 747 8280 PO Box 1154, Oranjestad Aruba, Dutch Caribbean Project Paradigm: Bringing the ICT tools for sustainable development to all stakeholders worldwide through collaborative research on applied mathematics, advanced modeling, software and standards development
Received on Wednesday, 21 August 2019 05:17:59 UTC