{
  "patent_number": "US 9361579",
  "country": "US",
  "title": "How Computers Calculate Probabilities in Large Knowledge Bases",
  "original_title": "Large scale probabilistic ontology reasoning",
  "summary": "A method for finding answers in a database of uncertain facts by ignoring probabilities to find a solution first, then calculating how likely that solution is based on the underlying evidence.",
  "what_it_does": "This patent describes a way to query a knowledge base where facts (axioms) come with a probability score. Instead of trying to calculate complex probabilities for the entire database at once, the system first ignores the probability scores to find a logical solution using standard reasoning. Once it identifies the 'justification'—the minimal set of facts needed to prove that answer—it then applies the probability scores only to that specific subset. This makes it computationally efficient to determine the 'net probability' of a conclusion in massive datasets that would otherwise be too slow to process.",
  "what_it_does_not_cover": [
    "Does not cover calculating probabilities for the entire knowledge base simultaneously without first finding a logical justification.",
    "Does not cover systems that lack a defined set of axioms or logical rules for deriving answers.",
    "Does not cover non-probabilistic reasoning systems that treat all facts as 100% certain."
  ],
  "filed": "2009-10-06",
  "granted": "2016-06-07",
  "expires": "2029-10-06",
  "status": "active",
  "holder": "International Business Machines Corp",
  "holder_url": "https://patentbrief.org/company/international-business-machines-corp",
  "inventors": [
    {
      "name": "Aditya Kalyanpur",
      "url": "https://patentbrief.org/inventor/aditya-kalyanpur"
    },
    {
      "name": "Achille B. Fokoue-Nkoutche",
      "url": "https://patentbrief.org/inventor/achille-b-fokoue-nkoutche"
    },
    {
      "name": "Kavitha Srinivas",
      "url": "https://patentbrief.org/inventor/kavitha-srinivas"
    },
    {
      "name": "Edith G. Schonberg",
      "url": "https://patentbrief.org/inventor/edith-g-schonberg"
    }
  ],
  "times_cited": 1,
  "tags": [
    "ai_ml",
    "software",
    "telecommunications"
  ],
  "abstract": "Techniques for computing a solution to a query formulated against a knowledge base (KB) are provided. The techniques include receiving a query formulated against a knowledge base, wherein the knowledge base comprises a set of one or more axioms, wherein each axiom is annotated with a specific probability value indicating a degree of certainty assigned thereto, ignoring each probability value of the one or more axioms and computing a solution to the query, computing each of one or more justifications for the query solution, wherein computing each of one or more justifications for the query solution comprises determining a minimal set of one or more axioms in the knowledge base that entail the query solution, and using each probability value of the one or more axioms in each justification to compute a net probability of an inferred query solution.",
  "url": "https://patentbrief.org/patent/us/9361579/large-scale-probabilistic-ontology-reasoning",
  "markdown_url": "https://patentbrief.org/patent/us/9361579/large-scale-probabilistic-ontology-reasoning/md",
  "google_patents_url": "https://patents.google.com/patent/US9361579",
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}