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Method for Ranking Users List Based on Tags and Text Analytics

IP.com Disclosure Number: IPCOM000247876D
Publication Date: 2016-Oct-09
Document File: 7 page(s) / 142K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed are a system and method to use cognitive and analytics technologies to create accurate filters to populate the recipient field of an email when the sender does not know the full name of the intended recipient. The proposed method uses text analytics and the tags of a user’s profile to rank email recipients within an organization's collaborative communication platform, and then presents the best match to the email sender.

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Method for Ranking Users List Based on Tags and Text Analytics

One challenge in sending email communication is that the sender might not have the full name of the recipient , especially if the recipient uses more than one name. The sender might know the name the recipient uses (e.g., a shortened version or nickname), but that might not be the name listed in an organization's directory. Thus, the sender has difficulty identifying the correct recipient.

With most email applications, when the sender begins entering the recipient's name in the destination (i.e., To:) field, the system automatically applies filters based on the beginning of the entry and searches for matches in the directory . When the name is common, however, the system can return too many results when the beginning of the name is the only filter.

The novel solution is to use cognitive and analytics technologies to create accurate filters in these use cases . The proposed method uses text analytics and the tags of a user's profile to rank email recipients within an organization 's collaborative communication platform. The method generates a ranking of the potential email recipients/candidates when the sender does not know the entered recipient's full name.

The general steps for the method follow:


1. Sender composes the email


2. Sender begins entering the recipient's name, or the part of the name, in the destination field


3. System queries the organization directory to filter names


4. Method calculates rankings for the l candidates and displays the list based on the rank (top-down). The mapping process:

A. Tags on the sender profile vs. tags in the mail vs. tags in the profile for the recipient


B. If tags on the mail are not defined, then the method can calculate the tags using known text analytics methods such as analysis of critical words
5. Sender can select the person ranked first as the most probable person that should receive the mail

In another embodiment, the system can send a warning to the email sender when the sender adds a person as a recipient that has a low probability of being the appropriate recipient.

The method to calculate the ranking for each potential receiver follows:

MT= Mail Tag

ST= Sender Tag

1


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RT= Receiver Tag

For every RT:

If RT exists in the MT, list then increase Rank
IF RT exists in the ST, list then increase Rank

For every Receiver Tag that coincides with the Mail Tag, the system adds a point value to the rank. In addition, for every Receiver Tag that coincides with the Sender Tag, the system adds another point to the Rank.

Current collaborative platforms use tags in profiles and other content; this is less used in email, but for the cases where emails are not tagged, the novel solution uses text analytics on email to define the tags.

Following is an example to automatically tag email using text analytics. Figure 1 is an example email.

Figure 1: Composed email to undergo text analytics

Once in the inbox, the system tag...