Abstract: Systems and methods for augmenting data by performing reject inference are disclosed. In one embodiment, the disclosed process trains an auto-encoder based on a subset of known labeled rows (e.g., non-default loan applicants). The process then infers labels for unlabeled rows using the auto-encoder (e.g., label some rows as non-default and some as default). The process then trains a machine learning model based on the known labeled rows and the inferred labeled rows. Applicant data is then processed by this new machine learning model to determine if a loan applicant is likely to default. If the loan applicant is not likely to default, the loan applicant is funded. For example, the loan applicant may be mailed a physical working credit card. However, if the loan applicant is likely to default, the loan applicant is rejected. For example, the loan applicant may be mailed a physical adverse action letter.

Abstract: An information retrieval system for automatically retrieving information related to the context of an active task being manipulated by a user. The system observes the operation of the active task and user interactions, and utilizes predetermined criteria to generate context representation of the active task that are relevant to the context of the active task. The information retrieval system then processes the context representation to generate queries or search terms for conducting an information search. The information retrieval system determines the relevance of a word to the context by utilizing an adaptive weighting system. The information retrieval system assigns varying weights to different attributes of a word and calculates an accumulated weight of the word by accumulating all weights assigned to the word. The attributes may include word size, style, location of the word, etc.

Abstract: An information retrieval system for automatically retrieving information related to the context of an active task being manipulated by a user. The system observes the operation of the active task and user interactions, and utilizes predetermined criteria to generate context representation of the active task that are relevant to the context of the active task. The information retrieval system then processes the context representation to generate queries or search terms for conducting an information search. The information retrieval system determines the relevance of a word to the context by utilizing an adaptive weighting system. The information retrieval system assigns varying weights to different attributes of a word and calculates an accumulated weight of the word by accumulating all weights assigned to the word. The attributes may include word size, style, location of the word, etc.

Abstract: An information retrieval system for automatically retrieving information related to the context of an active task being manipulated by a user. The system observes the operation of the active task and user interactions, and utilizes predetermined criteria to generate context representation of the active task that are relevant to the context of the active task. The information retrieval system then processes the context representation to generate queries or search terms for conducting an information search. The information retrieval system determines the relevance of a word to the context by utilizing an adaptive weighting system. The information retrieval system assigns varying weights to different attributes of a word and calculates an accumulated weight of the word by accumulating all weights assigned to the word. The attributes may include word size, style, location of the word, etc.

Abstract: An information retrieval system for automatically retrieving information related to the context of an active task being manipulated by a user. The system observes the operation of the active task and user interactions, and utilizes predetermined criteria to generate context representation of the active task that are relevant to the context of the active task. The information retrieval system then processes the context representation to generate queries or search terms for conducting an information search. The information retrieval system determines the relevance of a word to the context by utilizing an adaptive weighting system. The information retrieval system assigns varying weights to different attributes of a word and calculates an accumulated weight of the word by accumulating all weights assigned to the word. The attributes may include word size, style, location of the word, etc.

Abstract: An information retrieval system for automatically retrieving information related to the context of an active task being manipulated by a user. The system observes the operation of the active task and user interactions, and utilizes predetermined criteria to generate a context representation of the active task that are relevant to the context of the active task. The information retrieval system then processes the context representation to generate queries or search terms for conducting an information search. The information retrieval system reorders the terms in a query so that they occur in a meaningful order as they naturally occur in a document or active task being manipulated by the user. Furthermore, the information retrieval system may access a user profile to retrieve information related to the user, and the select information sources or transform search terms based on attributes related to the user, such as the user's occupation, position in a company, major in school, etc.

Abstract: An information retrieval system for automatically retrieving information related to the context of an active task being manipulated by a user. The system observes the operation of the active task and user interactions, and utilizes predetermined criteria to generate a context representation of the active task that are relevant to the context of the active task. The information retrieval system then processes the context representation to generate queries or search terms for conducting an information search. The information retrieval system reorders the terms in a query so that they occur in a meaningful order as they naturally occur in a document or active task being manipulated by the user. Furthermore, the information retrieval system may access a user profile to retrieve information related to the user, and the select information sources or transform search terms based on attributes related to the user, such as the user's occupation, position in a company, major in school, etc.

Abstract: An information retrieval system for automatically retrieving information related to the context of an active task being manipulated by a user. The system observes the operation of the active task and user interactions, and utilizes predetermined criteria to generate context representation of the active task that are relevant to the context of the active task. The information retrieval system then processes the context representation to generate queries or search terms for conducting an information search. The information retrieval system determines the relevance of a word to the context by utilizing an adaptive weighting system. The information retrieval system assigns varying weights to different attributes of a word and calculates an accumulated weight of the word by accumulating all weights assigned to the word. The attributes may include word size, style, location of the word, etc.

Abstract: An information retrieval system for automatically retrieving information related to the context of an active task being manipulated by a user. The system observes the operation of the active task and user interactions, and utilizes predetermined criteria to generate context representation of the active task that are relevant to the context of the active task. The information retrieval system then processes the context representation to generate queries or search terms for conducting an information search. The information retrieval system determines the relevance of a word to the context by utilizing an adaptive weighting system. The information retrieval system assigns varying weights to different attributes of a word and calculates an accumulated weight of the word by accumulating all weights assigned to the word. The attributes may include word size, style, location of the word, etc.

Abstract: An information retrieval system for automatically retrieving information related to the context of an active task being manipulated by a user. The system observes the operation of the active task and user interactions, and utilizes predetermined criteria to generate context representation of the active task that are relevant to the context of the active task. The information retrieval system then processes the context representation to generate queries or search terms for conducting an information search. The information retrieval system determines the relevance of a word to the context by utilizing an adaptive weighting system. The information retrieval system assigns varying weights to different attributes of a word and calculates an accumulated weight of the word by accumulating all weights assigned to the word. The attributes may include word size, style, location of the word, etc.

Abstract: An information retrieval system for automatically retrieving information related to the context of an active task being manipulated by a user. The system observes the operation of the active task and user interactions, and utilizes predetermined criteria to generate context representation of the active task that are relevant to the context of the active task. The information retrieval system then processes the context representation to generate queries or search terms for conducting an information search. The information retrieval system determines the relevance of a word to the context by utilizing an adaptive weighting system. The information retrieval system assigns varying weights to different attributes of a word and calculates an accumulated weight of the word by accumulating all weights assigned to the word. The attributes may include word size, style, location of the word, etc.

Abstract: A system and method in accordance with the present disclosure provide collateral information to a user receiving primary information via a first user interface. The system and method receives a user request for the collateral information. A context is defined from the primary information. A user's probable collateral information needs are derived from the context. The system and method then map the needs to one or more information repositories, and query the information repositories and retrieve collateral information satisfying the needs. The collateral information is presented via at least one user interface, which may include the first user interface. The system and method provide user controls via the at least one user interface to facilitate exploration of the collateral information by the user.

Abstract: An information retrieval system for automatically retrieving information related to the context of an active task being manipulated by a user. The system observes the operation of the active task and user interactions, and utilizes predetermined criteria to generate a context representation of the active task that are relevant to the context of the active task. The information retrieval system then processes the context representation to generate queries or search terms for conducting an information search. The information retrieval system reorders the terms in a query so that they occur in a meaningful order as they naturally occur in a document or active task being manipulated by the user. Furthermore, the information retrieval system may access a user profile to retrieve information related to the user, and the select information sources or transform search terms based on attributes related to the user, such as the user's occupation, position in a company, major in school, etc.

Abstract: An information retrieval system for automatically retrieving information related to the context of an active task being manipulated by a user. The system observes the operation of the active task and user interactions, and utilizes predetermined criteria to generate context representation of the active task that are relevant to the context of the active task. The information retrieval system then processes the context representation to generate queries or search terms for conducting an information search. The information retrieval system determines the relevance of a word to the context by utilizing an adaptive weighting system. The information retrieval system assigns varying weights to different attributes of a word and calculates an accumulated weight of the word by accumulating all weights assigned to the word. The attributes may include word size, style, location of the word, etc.

Abstract: An information retrieval system for automatically retrieving information related to the context of an active task being manipulated by a user. The system observes the operation of the active task and user interactions, and utilizes predetermined criteria to generate a context representation of the active task that are relevant to the context of the active task. The information retrieval system then processes the context representation to generate queries or search terms for conducting an information search. The information retrieval system reorders the terms in a query so that they occur in a meaningful order as they naturally occur in a document or active task being manipulated by the user. Furthermore, the information retrieval system may access a user profile to retrieve information related to the user, and the select information sources or transform search terms based on attributes related to the user, such as the users occupation, position in a company, major in school, etc.

Abstract: An information retrieval system for automatically retrieving information related to the context of an active task being manipulated by a user. The system observes the operation of the active task and user interactions, and utilizes predetermined criteria to generate context representation of the active task that are relevant to the context of the active task. The information retrieval system then processes the context representation to generate queries or search terms for conducting an information search. The information retrieval system determines the relevance of a word to the context by utilizing an adaptive weighting system. The information retrieval system assigns varying weights to different attributes of a word and calculates an accumulated weight of the word by accumulating all weights assigned to the word. The attributes may include word size, style, location of the word, etc.

Abstract: Methods and apparatus assessing, ranking, organizing, and presenting search results associated with a user's current work context are disclosed. The system disclosed assesses, ranks, organizes and presents search results against a user's current work context by comparing statistical and heuristic models of the search results to a statistical and heuristic model of the user's current work context. In this manner, search results are assessed, ranked, organized, and/or presented with the benefit of attributes of the user's current work context that are predictive of relevance, such as words in a user's document (e.g., web page or word processing document) that may not have been included in the search query. In addition, search results from multiple search engines are combined into an organization scheme that best reflects the user's current task. As a result, lists of search results from different search engines can be more usefully presented to the user.

Abstract: Methods and apparatus assessing, ranking, organizing, and presenting search results associated with a user's current work context are disclosed. The system disclosed assesses, ranks, organizes and presents search results against a user's current work context by comparing statistical and heuristic models of the search results to a statistical and heuristic model of the user's current work context. In this manner, search results are assessed, ranked, organized, and/or presented with the benefit of attributes of the user's current work context that are predictive of relevance, such as words in a user's document (e.g., web page or word processing document) that may not have been included in the search query. In addition, search results from multiple search engines are combined into an organization scheme that best reflects the user's current task. As a result, lists of search results from different search engines can be more usefully presented to the user.

Abstract: Methods and apparatus assessing, ranking, organizing, and presenting search results associated with a user's current work context are disclosed. The system disclosed assesses, ranks, organizes and presents search results against a user's current work context by comparing statistical and heuristic models of the search results to a statistical and heuristic model of the user's current work context. In this manner, search results are assessed, ranked, organized, and/or presented with the benefit of attributes of the user's current work context that are predictive of relevance, such as words in a user's document (e.g., web page or word processing document) that may not have been included in the search query. In addition, search results from multiple search engines are combined into an organization scheme that best reflects the user's current task. As a result, lists of search results from different search engines can be more usefully presented to the user.

Abstract: Methods and apparatus assessing, ranking, organizing, and presenting search results associated with a user's current work context are disclosed. The system disclosed assesses, ranks, organizes and presents search results against a user's current work context by comparing statistical and heuristic models of the search results to a statistical and heuristic model of the user's current work context. In this manner, search results are assessed, ranked, organized, and/or presented with the benefit of attributes of the user's current work context that are predictive of relevance, such as words in a user's document (e.g., web page or word processing document) that may not have been included in the search query. In addition, search results from multiple search engines are combined into an organization scheme that best reflects the user's current task. As a result, lists of search results from different search engines can be more usefully presented to the user.