Method and mechanism for superpositioning state vectors in a semantic abstract
First Claim
Patent Images
1. A computer-implemented method for constructing a single vector representing a semantic abstract in a topological vector space for a semantic content of a document on a computer system, the method comprising:
- storing a semantic content for the document in computer memory accessible by the computer system;
identifying a directed set of concepts as a dictionary, the directed set including a maximal element at least one concept, and at least one chain from the maximal element to every concept;
selecting a subset of the chains to form a basis for the dictionary;
identifying lexemes/lexeme phrases in the semantic content;
measuring how concretely each lexemes/lexeme phrase is represented in each chain in the basis and the dictionary;
constructing state vectors in the topological vector space for the semantic content using the measures of how concretely each lexemes/lexeme phrase is represented in each chain in the dictionary and the basis;
superpositioning the state vectors to construct the single vector; and
comparing the single vector with a second semantic abstract for a second document to determined whether the second document is semantically close to the document.
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Abstract
State vectors representing the semantic content of a document are created. The state vectors are superpositioned to construct a single vector representing a semantic abstract for the document. The single vector can be normalized. Once constructed, the single vector semantic abstract can be compared with semantic abstracts for other documents to measure a semantic distance between the documents, and can be used to locate documents with similar semantic content.
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Citations
21 Claims
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1. A computer-implemented method for constructing a single vector representing a semantic abstract in a topological vector space for a semantic content of a document on a computer system, the method comprising:
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storing a semantic content for the document in computer memory accessible by the computer system; identifying a directed set of concepts as a dictionary, the directed set including a maximal element at least one concept, and at least one chain from the maximal element to every concept; selecting a subset of the chains to form a basis for the dictionary; identifying lexemes/lexeme phrases in the semantic content; measuring how concretely each lexemes/lexeme phrase is represented in each chain in the basis and the dictionary; constructing state vectors in the topological vector space for the semantic content using the measures of how concretely each lexemes/lexeme phrase is represented in each chain in the dictionary and the basis; superpositioning the state vectors to construct the single vector; and comparing the single vector with a second semantic abstract for a second document to determined whether the second document is semantically close to the document. - View Dependent Claims (2, 3, 4, 5, 19, 20)
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6. A computer-readable medium containing a program to construct a single vector representing a semantic abstract in a topological vector space for a semantic content of a document on a computer system, the program comprising:
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storing a semantic content for the document in computer memory accessible by the computer system; identifing a directed set of concepts as a dictionary, the directed set including a maximal element at least one concept, and at least one chain from the maximal element to every concept; selecting a subset of the chains to form a basis for the dictionary; identifing lexemes/lexeme phrases in the semantic content; measuring how concretely each lexemes/lexeme phrase is represented in each chain in the basis and the dictionary; constructing state vectors in the topological vector space for the semantic content using the measures of how concretely each lexemes/lexeme phrase is represented in each chain in the dictionary and the basis; superpositioning the state vectors to construct the single vector; and storing the single vector as the semantic abstract for the document. - View Dependent Claims (7, 8, 9, 10)
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11. An apparatus on a computer system to construct a single vector representing a semantic abstract in a topological vector space for a semantic content of a document on a computer system, the apparatus comprising:
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a semantic content stored in a memory of the computer system; a lexeme identifier adapted to identify lexemes/lexeme phrases in the semantic content; a state vector constructor for constructing state vectors in the topological vector space for each lexeme/lexeme phrase identified by the lexeme identifier, the state vectors measuring how concretely each lexeme/lexeme phrase identified by the lexeme identifier is represented in each chain in a basis and a dictionary, the dictionary including a directed set of concepts including a maximal element and at least one chain from the maximal element to every concept in the directed set, the basis including a subset of chains in the directed set; and a superpositioning unit adapted to superposition the state vectors into a single vector as the semantic abstract. - View Dependent Claims (12, 13, 14, 15)
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16. A computer-implemented method for constructing minimal vectors representing a semantic abstract in a topological vector space for a semantic content of a document on a computer system, the method comprising:
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storing a semantic content for the document in computer memory accessible by the computer system; identifying a directed set of concepts as a dictionary, the directed set including a maximal element at least one concept, and at least one chain from the maximal element to every concept; selecting a subset of the chains to form a basis for the dictionary; identifying lexemes/lexeme phrases in the semantic content; measuring how concretely each lexemes/lexeme phrase is represented in each chain in the basis and the dictionary; constructing state vectors in the topological vector space for the semantic content using the measures of how concretely each lexemes/lexeme phrase is represented in each chain in the dictionary and the basis; locating clumps of state vectors in the topological vector space; superpositioning the state vectors within each clump to form a single vector representing the clump; collecting the single vectors representing each clump to form the minimal vectors; and storing the minimal vectors as the semantic abstract for the document.
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17. A computer-readable medium containing a program to construct minimal vectors representing a semantic abstract in a topological vector space for a semantic content of a document on a computer system, the program executable by a computer and implementing:
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storing a semantic content for the document in computer memory accessible by the computer system; identifing a directed set of concepts as a dictionary, the directed set including a maximal element at least one concept, and at least one chain from the maximal element to every concept; selecting a subset of the chains to form a basis for the dictionary; identifing lexemes/lexeme phrases in the semantic content; measuring how concretely each lexemes/lexeme phrase is represented in each chain in the basis and the dictionary; constructing state vectors in the topological vector space for the semantic content using the measures of how concretely each lexemes/lexeme phrase is represented in each chain in the dictionary and the basis; locating clumps of state vectors in the topological vector space; superpositioning the state vectors within each clump to form a single vector representing the clump; collecting the single vectors representing each clump to form the minimal vectors; and storing the minimal vectors as the semantic abstract for the document.
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18. An apparatus on a computer system to construct minimal vectors representing a semantic abstract in a topological vector space for a semantic content of a document on a computer system, the apparatus comprising:
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a semantic content stored in a memory of the computer system; a state vector constructor for constructing state vectors in the topological vector space for each lexeme/lexeme phrase in the semantic content the state vectors measuring how concretely each lexeme/lexeme phrase is represented in each chain in a basis and a dictionary, the dictionary including a directed set of concepts including a maximal element and at least one chain from the maximal element to every concept in the directed set, the basis including a subset of chains in the directed set; a clump locator unit adapted to locate clumps of state vectors in the topological vector space; a superpositioning unit adapted to superposition the state vectors within each clump into a single vector representing the clump; and a collection unit adapted to collect the single vectors representing the clump into the minimal vectors of the semantic abstract.
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21. An apparatus, comprising:
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means for storing a semantic content for a document in computer memory accessible by a computer system; means for identifying a directed set of concepts as a dictionary, the directed set including a maximal element at least one concept, and at least one chain from the maximal element to every concept; means for selecting a subset of the chains to form a basis for the dictionary; means for identifying lexemes/lexeme phrases in the semantic content; means for measuring how concretely each lexemes/lexeme phrase is represented in each chain in the basis and the dictionary; means for constructing state vectors in the topological vector space for the semantic content using the measures of how concretely each lexemes/lexeme phrase is represented in each chain in the dictionary and the basis; means for locating clumps of state vectors in the topological vector space; means for superpositioning the state vectors within each clump to form a single vector representing the clump; means for collecting the single vectors representing each clump to form the minimal vectors; and means for storing the minimal vectors as the semantic abstract for the document.
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Specification