International Business Machines Corporation

Srinivas Varma Chitiveli

Barton Wayne Emanuel

Michael E Moran

Alexander Wolcott Holt

Joshua Fox

Josemina Marcella Magdalen

Eric B Libow

Sathiskumar Palaniappan

Michael Pelts

Prasanna Alur Mathada

A method for providing an interactive elevator assistant is provided. The method may include identifying amenities associated with a property and location-based features within a vicinity of the property. The method may further include mapping the amenities to floor levels associated with the property. The method may further include receiving user input from a user located on an elevator associated with the property. The method may further include, in response to determining that the received user input comprises an amenity, determine the one or more floor levels on the property that are associated with the amenity and triggering the elevator to navigate to the determined one or more floor levels. The method may also include, in response to determining that the received user input comprises a location-based feature, sending the received user input to an application for processing. The method may further include providing a response via the elevator.

Cognitive interactive elevator assistant

Provided are a computer program product, method, and system for rendering search results. A search request is received having a search criteria to perform with respect to objects having content instances. A determination is made of the objects having qualifying content instances that satisfy the search criteria, an attribute value of the qualifying content instances for a specified attribute, and appearance settings for the qualifying content instances based on the determined attribute values. The appearance settings vary based on the attribute values. Tags are generated indicating the content instances and appearance settings for the content instances. A visualization of the tags in a display group are generated to provide visualization of the qualifying content instances in the objects according to the appearance settings, wherein visualizations of the tags is varied based on the determined appearance settings.

Generating visualizations of a display group of tags representing content instances in objects satisfying a search criteria

Provided are techniques for displaying search results in a first page, receiving feedback from the user that indicate which of the search results in the first page are at least one of relevant and irrelevant, re-ordering the search results in a second page based on the indications of the search results in the first page, and displaying the re-ordered search results in the second page.

Iterative refinement of search results based on user feedback

Provided is a method for rendering search results. A search request is received having a search criteria to perform with respect to objects having content instances. A determination is made of the objects having qualifying content instances that satisfy the search criteria, an attribute value of the qualifying content instances for a specified attribute, and appearance settings for the qualifying content instances based on the determined attribute values. The appearance settings vary based on the attribute values. Tags are generated indicating the content instances and appearance settings for the content instances. A visualization of the tags in a display group are generated to provide visualization of the qualifying content instances in the objects according to the appearance settings, wherein visualizations of the tags is varied based on the determined appearance settings.

Systems, methods and articles of manufacture are disclosed for identifying a training document for a content classifier. One or more thresholds may be defined for designating a document as a training document for a content classifier. A plurality of documents may be evaluated to compute a score for each respective document. The score may represent suitability of a document for training the content classifier with respect to a category. The score may be computed based on content of the plurality of documents, metadata of the plurality of documents, link structure of the plurality of documents, user feedback (e.g., user supplied document tags) received for the plurality of documents, and document metrics received for the plurality of documents. Based on the computed scores, a training document may be selected. The content classifier may be trained using the selected training document.

Identifying training documents for a content classifier

Systems, methods and articles of manufacture are disclosed for detecting a duplicate document. A plurality of documents may be assigned to categories, each category corresponding to a collection of duplicates, or near duplicate documents. A new document may be received. The new document may be evaluated against each category to determine a similarity score between the new document and each category. The new document may be identified as a duplicate based on the similarity scores and thresholds for each category. An action may then be performed on the duplicate based on duplication rules. The thresholds and duplication rules may be customized by a user.

Detecting duplicate documents using classification

Systems, methods and articles of manufacture are disclosed for generating search results based on user feedback. A request may be received to generate search results retrieved using a search string. The request may include user feedback for one or more selected documents of the search results. Improved search results may be generated based on the search results and the feedback for one or more selected documents of the search results. The improved search results may be output to a graphical display device.

Generating search results based on user feedback

Classifying electronic mail (e-mail) based on content and predefined categories. Content of a received e-mail may be analyzed to determine one of a plurality of predefined categories into which the e-mail is classified. A relevancy score may also be calculated to indicate the strength of correlation between the e-mail and the category. A user may be allowed to sort e-mails in an e-mail box based on the category names and/or relevancy scores.

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Germantown, MD, United States of America

Srinivas Varma Chitiveli