Browse Prior Art Database

Temporally Relevant Activity Stream Augmentation

IP.com Disclosure Number: IPCOM000246601D
Publication Date: 2016-Jun-20
Document File: 3 page(s) / 117K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a system that augments an activity stream with temporally relevant content in order to ensure that the user receives the most relevant messages or feeds from an email inbox, social network wall, activity stream, timeline, or profile. This system eliminates the filter bubble that defines a user’s search terms and temporally drives significance.

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Page 01 of 3

Temporally Relevant Activity Stream Augmentation

Mail clients and online social networks are the universal mechanism to connect people and information in logical and organized ways that enable sharing and processing of information between the users. The most common mechanisms of sharing and processing information are the email inbox, social network wall, activity stream, timeline, or profile. These mechanisms enable a user to rapidly share information with others and gather information from others in the networks. The mechanisms have resulted in an explosion in the number of messages that must be shared each day.

As individuals establish distribution lists and subscriptions to content, hundreds of messages are missed because the messages do not penetrate the individual's filter bubble.

There is a clear need to avoid the narrow acquisition of information due to the filter bubble.

The novel system augments an activity stream with temporally relevant content, by:


• Identifying a portion of an activity stream to devote to invisible/unknown messages

• Analyzing active search terms from the user's social network (crowd-sourced)
• Selecting a portion of the messages matching search terms from the social network (user's/entire)


• Augmenting the social message list with a portion of messages

The system may limit the content to information presented within a short period (e.g., one hour, one minute, 15 minutes, one day, one week, etc.). The system is used with collaboration systems, project management systems, and social systems such as:

• Social networking
• Asynchronous networks

• Synchronous networks • Email • Real Time Instant Messaging • Instant Messaging • Wikis
• Other project/task systems

Identifying a Portion of an Activity Stream to Devote to Invisible/Unknown Messages

1. The user requests a view of the social network updates 2. The user, organization, or system administrator sets the total number of messages to devote to messages from outside the filter bubble. For example:

• User A sets 10% for the organization • User B sets 10% for himself
• The System Administrator sets 10%

3. The messages may be invisible messages (filtered out) and/or unknown messages (otherwise not seen)

4. The user may select to ignore invisible messages, as those messages are intentionally left out

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Analyzing Active Search Terms from the User's Social Network (Crowd-Sourced)

1. The system records all searches in the social network (Search Terms - User - Time/Date of Search), and may:

A. Consider other social metadata in the analysis (e.g., likes, recommendations, comments, visits, hashtags, etc.)

B. Normalize hashtags to the normal form word, remove @mentions, or stem the search terms

C. Use synonyms for the search terms

D. Store the normal form of the internal search logic (e.g., Patriots Boston may be represented internally as Patriot (singular), Boston may be "New England" as a synonym)

E. Limit the c...