International Business Machines Corporation

Erika Varga

Scott Howard Prager

Vijay Francis

Cameron J Bosnic, Jr

Jacob M Lineberry

Kristina Beckley

Jodi Rajaniemi

Jonathan Frederick Brunn

Ethan L Perry

Jennifer E Heins

Marc D Labrecque

Mary E Miller

A computer determines a filtering query based on a persistent list of items, wherein the persistent list of items comprises a list of natural language elements, and wherein the filtering query is computer instructions corresponding to the natural language elements. The computer determines whether a server is capable of receiving the filtering query. Based on determining that the server is capable of receiving the filtering query, the computer transmits the filtering query to the server. The computer receives filtered content from the server, wherein the filtered content is based on the filtering query, and the computer displays the filtered content.

Persistent filter content refinement system

Mapping and obscuring digital representations of a number of user accounts on a social network map includes identifying a primary user account from a number of user accounts of a social network, determining, based on metadata associated with the user accounts, a relationship for each of the user accounts relative to the primary user account, mapping, based on the relationship for each of the user accounts relative to the primary user account, a digital representation of each of the user accounts to a territory on a social network map, determining, based on the relationship for each of the user accounts relative to the primary user account, an obscurity level for each of the user accounts, and obscuring, based on the obscurity level, the territory associated with the digital representation of each of the user accounts on a social network map from the primary user account.

Mapping and obscuring digital representations of a number of user accounts on a social network map

Presenting a reviewer feedback of a document, one aspect, may comprise retrieving a plurality of feedback on a document, each feedback having an associated reviewer who provided the feedback. Social data associated with the reviewer of the feedback may be obtained. A plurality of characteristics associated with the feedback may be identified, at least some of the characteristics identified based on the social data. The characteristics may include at least the associated reviewer's position in an organization hierarchy, the reviewer's expertise, frequency of the feedback, impact of the feedback, and usefulness of the feedback. The plurality of feedback may be prioritized based on the plurality of characteristics, and a list of prioritized feedback may be presented via a user interface.

Using social data to assist editors in addressing reviewer feedback in a document review workflow

The present disclosure provides for automatically detecting groups of people who may be interested in different types of content (e.g., different presentations, different presentation sections, different presentation styles). Further, the present disclosure provides for automatically providing presentation filters appropriate for each group of people.

Profile driven presentation content displaying and filtering

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Harvard, MA, United States of America

Erika Varga