System and for to determine diverse and relevant passages of documents

A method for content relevance search, comprising:

• receiving content and a relevance model related to the content, the relevance model comprising:
• a plurality of features;
• and
• a relevance value weight for each feature;
• processing the content to generate a plurality of search results based on the plurality of features in the relevance model, each of the search results comprising one or more of the features in the relevance model;
• generating an initial score for each of the search results using the relevance model, the initial score for each of the search results being calculated by:
• determining a sum of the relevance value weights of the one or more features comprised in the search result;
• multiplying the sum by a number of unique features within the search result, thereby generating a multiplied sum;
• and
• dividing the multiplied sum by a positional spread value, the positional spread value determined based on a distance between a first position of a first feature in the search result and a second position of a second feature in the search result, wherein the number of unique features comprise the first and second features;
• based on the generation of the initial score for each search result, selecting an initial one of the search results;
• modifying the relevance value weight of each feature comprised in the initial one of the search results, by the relevance value weight of each feature comprised in the initial one of the search results;
• generating a subsequent score for each search result other than the initial one of the search results, wherein the subsequent score for each search result of the remaining search results is generated using the relevance mode and is based on:
• the one or more features comprised in each remaining search result;
• the number of unique features within each remaining search result;
• the positional spread of features within each remaining search result;
• and
• the relevance value weights of the one of more features comprised in each remaining search result, the relevance value weights being sourced from the relevance model, wherein the relevance model incorporates the relevance value weight of each feature that was comprised in the initial one of the search results;
• and
• based on the generation of the subsequent score for each remaining search result, selecting a subsequent search result from all of the remaining search results, the subsequent search result and the initial search result characterized by diverse and relevant ones of the features.

A non-transitory computer readable medium, comprising:

• receiving content and a relevance model related to the content, the relevance model comprising:
• a plurality of features;
• and
• a relevance value weight for each feature;
• processing the content to generate a plurality of search results based on the plurality of features in the relevance model, each of the search results comprising one or more of the features in the relevance model;
• generating an initial score for each of the search results using the relevance model, the initial score for each of the search results being calculated by:
• determining a sum of the relevance value weights of the one or more features comprised in the search result;
• multiplying the sum by a number of unique features within the search result, thereby generating a multiplied sum;
• and
• dividing the multiplied sum by a positional spread value, the positional spread value determined based on a distance between a first position of a first feature in the search result and a second position of a second feature in the search result, wherein the number of unique features comprise the first and second features;
• based on the generation of the initial score for each search result, selecting an initial one of the search results;
• modifying the relevance value weight of each feature comprised in the initial one of the search results, by reducing the relevance value weight of each feature comprised in the initial one of the search results;
• generating a subsequent score for each search result other than the initial one of the search results, wherein the subsequent score for each search result of the remaining search results is generated using the relevance mode and is based on:
• the one or more features comprised in each remaining search result;
• the number of unique features within each remaining search result;
• the positional spread of features within each remaining search result;
• and
• the relevance value weights of the one of more features comprised in each remaining search result, the relevance value weights being sourced from the relevance model, wherein the relevance model incorporates the relevance value weight of each feature that was comprised in the initial one of the search results;
• and
• based on the generation of the subsequent score for each remaining search result, selecting a subsequent search result from all of the remaining search results, the subsequent search result and the initial search result characterized by diverse and relevant ones of the features.