US 8,180,783 B1Granted

Document ranking systems and methods

AssigneeSoftek Solutions, Inc.

InventorsDavid C. Fletcher, Doug R. Wagers

Life of this patent

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Abstract

Systems and methods are provided for ranking document data retrieved from a data source in response to a search request. A ranking system retrieves document data from documents in the data source that each includes at least one key term that matches a search term in the search request. For each document, a term frequency value is calculated based on a number of occurrences of the key term in the document. Prefix and suffix term rules are used to determine whether a particular occurrence of the key term in a particular document should be included in determining a term weight value for that particular occurrence of the key term. A relevancy ranking value is determined for each document based on the corresponding term frequency and term weight values. The document data is displayed according to each document's corresponding relevancy ranking value.

Claims34

Dependent claims

A ranking system comprising:

a memory comprising at least one negation term;
a processor comprising:
a document ranking application comprising modules executable by the processor to process a plurality of documents retrieved from a data source, the document ranking application comprising:
a token generation module to generate a corresponding token for each word in document data included in at least one of the plurality of documents;
and
a tagging module to:
retrieve the at least one negation term and at least one negation rule from the memory;
compare the at least one negation term according to the at least one negation rule to other terms in the document data that are within a selected proximity of each word;
assign a negative tag to the corresponding token for a particular word if the at least one negation term matches any other terms within the selected proximity of the particular word according to the negation rule;
assign a positive tag to the corresponding token for the particular word if the at least one negation term does not match any of the other terms within the selected proximity of the particular word according to the negation rule;
and
store processed document data for the at least one document in a data store, the processed document data comprising document content, tokens, and the tags assigned to each of the tokens;
a document data display application comprising modules executable by the processor to generate processed document data for display in response to a search request, the document data display application comprising:
a token analysis module to:
receive the search request including document identification data;
identify the processed document data in the data store that corresponds to the document identification data;
and
search the processed document data for tokens that have been assigned the positive context tag;
and
a display module to generate the processed document data for display that includes visual indicators for each word where the corresponding token is assigned the positive context tag.

17 more elements

A ranking system comprising:

a memory comprising at least one negation term;
a processor comprising:
a document ranking application comprising modules executable by the processor to process a plurality of documents retrieved from a data source, the document ranking application comprising:
a token generation module to generate a corresponding token for each word in document data included in at least one of the plurality of documents;
and
a tagging module to:
retrieve the at least one negation term from the memory;
compare the at least one negation term to other terms included in the document data for the at least one document that are within a selected proximity of each word;
assign a negative tag to the corresponding token for a particular word if the at least one negation term matches any other terms within the selected proximity of the particular word;
assign a positive tag to the corresponding token for the particular word if the at least one negation term does not match any of the other terms within the selected proximity of the particular word;
and
store processed document data for the at least one document in a data store, the processed document data comprising document content, tokens, and the tags assigned to each of the tokens;
a document data display application comprising modules executable by the processor to display document data retrieved from the data store in response to a search request, the document data display application comprising:
a token analysis module to:
receive the search request comprising document identification data;
identify the processed document data in the data store that corresponds to the document identification data;
and
search the processed document data for tokens assigned the positive context tag;
and
a display module generates the processed document data for display with visual indicators for each word where the corresponding token is assigned the positive context tag;
and
an analytics application comprising modules executable by the processor to analyze the processed document data retrieved from the data store in response to another search request, the analytics application comprising:
an analytics module to:
receive the other search request comprising at least one of the document identification data and document preparer identification data;
identify predictive document data and corresponding result documents data from the processed document data in the data store that correspond to the at least one of the document identification data and the document preparer identification data;
identify corresponding tokens in the predictive document data and the corresponding result document data that correspond to the same particular word and identify the tags assigned to each of the identified corresponding tokens;
assign an accuracy rating to the predictive document data based on the tags assigned to each of the identified corresponding tokens, wherein the accuracy rating has a first value when each of the identified corresponding tokens are both assigned the positive context tag, and wherein the accuracy rating has a second value when one of the identified corresponding tokens is assigned the positive context tag and another one of identified corresponding tokens is assigned the negative context tag;
and
store the accuracy rating for the particular predictive document in the memory.

26 more elements

A ranking method comprising:

generating, at least one processor, a corresponding token for each word in document data included in at least one of a plurality of documents;
retrieving, at the at least one processor, at least one negation term and at least one negation rule from a memory;
comparing, at the at least one processor, the at least one negation term according to the at least one negation rule to other terms in the document data that are within a selected proximity of each word;
assigning, at the at least one processor, a negative tag to the corresponding token for a particular word if the at least one negation term matches any other terms within the selected proximity of the particular word according to the negation rule;
assigning, at the at least one processor, a positive tag to the corresponding token for the particular word if the at least one negation term does not match any of the other terms within the selected proximity of the particular word according to the negation rule;
storing processed document data for the at least one document in a data store, the processed document data comprising document content, tokens, and the tags assigned to each of the tokens;
receiving a search request including document identification data;
identifying, at the at least one processor, processed document data in the data store that corresponds to the document identification data;
searching, at the at least one processor, the processed document data for tokens that have been assigned the positive context tag;
and
generating the processed document data for display that includes visual indicators for each word where the corresponding token is assigned the positive context tag.

8 more elements

A ranking method comprising:

generating, at least one processor, a corresponding token for each word in document data included in at least one of a plurality of documents;
retrieving, at the at least one processor, at least one negation term from a memory;
comparing, at the at least one processor, the at least one negation term to other terms included in the document data for the at least one document that are within a selected proximity of each word;
assigning, at the at least one processor, a negative tag to the corresponding token for a particular word if the at least one negation term matches any other terms within the selected proximity of the particular word;
assigning, at the at least one processor, a positive tag to the corresponding token for the particular word if the at least one negation term does not match any of the other terms within the selected proximity of the particular word;
storing processed document data for the at least one document in a data store, the processed document data comprising document content, tokens, and the tags assigned to each of the tokens;
receiving a search request comprising document identification data;
identifying the processed document data in the data store that corresponds to the document identification data;
searching the processed document data for tokens assigned the positive context tag;
generating the processed document data for display with visual indicators for each word where the corresponding token is assigned the positive context tag;
receiving another search request comprising at least one of the document identification data and document preparer identification data;
identifying predictive document data and corresponding result documents data from the processed document data in the data store that correspond to the at least one of the document identification data and the document preparer identification data;
identifying corresponding tokens in the predictive document data and the corresponding result document data that correspond to the same particular word;
identifying the tags assigned to each of the identified corresponding tokens;
assigning an accuracy rating to the predictive document data based on the tags assigned to each of the identified corresponding tokens, wherein the accuracy rating has a first value when each of the identified corresponding tokens are both assigned the positive context tag, and wherein the accuracy rating has a second value when one of the identified corresponding tokens is assigned the positive context tag and another one of identified corresponding tokens is assigned the negative context tag;
and
storing the accuracy rating for the particular predictive document in the memory.

14 more elements

A non-transitory computer-readable medium encoded with instructions executable by at least one processor to:

generate a corresponding token for each word in document data included in at least one of a plurality of documents;
retrieve at least one negation term from a memory;
compare the at least one negation term to other terms included in the document data for the at least one document that are within a selected proximity of each word;
assign a negative tag to the corresponding token for a particular word if the at least one negation term matches any other terms within the selected proximity of the particular word;
assign a positive tag to the corresponding token for the particular word if the at least one negation term does not match any of the other terms within the selected proximity of the particular word;
store processed document data for the at least one document in a data store, the processed document data comprising document content, tokens, and the tags assigned to each of the tokens;
receive a search request comprising document identification data;
identify the processed document data in the data store that corresponds to the document identification data;
search the processed document data for tokens assigned the positive context tag;
generate the processed document data for display with visual indicators for each word where the corresponding token is assigned the positive context tag;
receive another search request comprising at least one of the document identification data and document preparer identification data;
identify predictive document data and corresponding result documents data from the processed document data in the data store that correspond to the at least one of the document identification data and the document preparer identification data;
identify corresponding tokens in the predictive document data and the corresponding result document data that correspond to the same particular word and identify the tags assigned to each of the identified corresponding tokens;
assign an accuracy rating to the predictive document data based on the tags assigned to each of the identified corresponding tokens, wherein the accuracy rating has a first value when each of the identified corresponding tokens are both assigned the positive context tag, and wherein the accuracy rating has a second value when one of the identified corresponding tokens is assigned the positive context tag and another one of identified corresponding tokens is assigned the negative context tag;
and
store the accuracy rating for the particular predictive document in the memory.

13 more elements

Dependencies are inferred from the claim text.