Evidence map›Paper›PMID 26582967›Full record

ArticleLogic journal of the IGPL2015

Reasoning with Vectors: A Continuous Model for Fast Robust Inference.

Dominic Widdows, Trevor Cohen

Abstract read
In one paragraph

Article in Logic journal of the IGPL, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Vector Symbolic Architectures as a Computing Framework for Emerging Hardware.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2022
    Article
  5. Article
  6. Article
  7. Semantics in High-Dimensional Space.Frontiers in artificial intelligence · 2021
    Review
  8. Article
  9. Exploring Novel Computable Knowledge in Structured Drug Product Labels.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2020
    Article
  10. Medical Information Extraction Model for User-generated Content.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2019
    Article
  11. Article
  12. Article
  13. Article
  14. Rediscovering Don Swanson: the Past, Present and Future of Literature-Based Discovery.Journal of data and information science (Warsaw, Poland) · 2017
    Article
  15. Embedding of semantic predications.Journal of biomedical informatics · 2017
    Article
  16. Literature-Based Discovery of Confounding in Observational Clinical Data.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Dominic WiddowsMicrosoft Bing.
Trevor CohenUniversity of Texas School of Biomedical Informatics at Houston.

Funding

Using Biomedical Knowledge to Identify Plausible Signals for PharmacovigilanceR01LM011563 · NLM · UNIVERSITY OF WASHINGTON · PI COHEN, TREVOR · 2013 to 2020
$3.0M
Encoding Semantic Knowledge in Vector Space for Biomedical InformationR21LM010826 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI COHEN, TREVOR · 2010 to 2011
$402k
NLM NIH HHS R01 LM011563NLM NIH HHS R21 LM010826
6 · The paper itself

Abstract

This paper describes the use of continuous vector space models for reasoning with a formal knowledge base. The practical significance of these models is that they support fast, approximate but robust inference and hypothesis generation, which is complementary to the slow, exact, but sometimes brittle behavior of more traditional deduction engines such as theorem provers. The paper explains the way logical connectives can be used in semantic vector models, and summarizes the development of Predication-based Semantic Indexing, which involves the use of Vector Symbolic Architectures to represent the concepts and relationships from a knowledge base of subject-predicate-object triples. Experiments show that the use of continuous models for formal reasoning is not only possible, but already demonstrably effective for some recognized informatics tasks, and showing promise in other traditional problem areas. Examples described in this paper include: predicting new uses for existing drugs in biomedical informatics; removing unwanted meanings from search results in information retrieval and concept navigation; type-inference from attributes; comparing words based on their orthography; and representing tabular data, including modelling numerical values. The algorithms and techniques described in this paper are all publicly released and freely available in the Semantic Vectors open-source software package.

Identifiers

PMID26582967
PMCPMC4646228

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.