- About this Module
- Add Rules
- Name
- Type
- Priority
- Criteria
- Groups
- Source Field
- Field Value
- Comparison Type
- Target Field
- Two Way Matching
- Example Screenshots
- Target Field Value
About this Module
The Recommendation Module allows you to set up a Business Matchmaking matrix to connect attendees, speakers, sponsors/exhibitors, and propose conference sessions based on their interests.
This module serves as an "inlet" for the matrix. Once set up, you can create a Recommendation block in the livepages to display the recommendations.
Add Rules
Clicking on the "Add Rule" button gives you a pop up on the right-hand side as shown below:
Name
Give a Name to the Rule that you are setting.
Type
To select the relevant Rule Types from the drop-down:
- People to People
The rule is for Participants Networking.
- People to Session
The rule is for Session Matching.
- People to Products
The rule is for Product Matching.
- People to Sponsor
The rule is for Sponsor company Matching (Not to be confused with sponsor people which is catered by People to People type).
Priority
The priority that you would like to give to this rule
Rule with priority 1 will have the highest priority / importance / weight and will be lower as the priority field value increases. Rules can also have equal priorities.
Criteria
This option allows us to select any one out of the 3 different criteria for recommendations:
- Inclusion - A normal recommendation rule
- Exclusion - A rule to exclude a particular set of attendees, sessions, products, or sponsors from being recommended to another set of attendees.
- ExcludeAll - A rule to completely exclude a set of attendees, sessions, products, or sponsors from recommendations
NOTE: Criteria will soon be available for the all types of rules.
Groups
Groups can be created in cases where it is required to apply a single or multiple rules to a particular group of Attendees.
Source Field
This can be any one of the fields, available to people on the registration forms.
Example:
If you select Job Title, it will use the values from the Job Title field as source to match with that of theĀ target field.
Field Value
If you want to recommend some specific source value to specific target value then you can specify the source value in this text field.
Leave this text field empty if you want all possible source values to be used for comparison.
Comparison Type
- Exact Match
- Also known as Syntactic Match. This will generate recommendations for every exact match between source and target values.
- Semantic Match
- In general, semantic means the meaning of a word or a sentence. In this type, the text semantics in the source and target values will be compared using NLP techniques.
Target Field
The target field values are compared with the source field values to generate recommendations.
Example:
If you select Job Title, it will use the values from the Job Title field as the target to match with that of theĀ source field.
Two Way Matching
In Rules where Source Field and Target Fields are specified only the Target will be recommended to the Source. Two-Way-Matching allows us to recommend "Source to Target" in addition to the usual "Target to Source".
NOTE: Two Way Matching is available only for the People to People type.
Example Screenshots
In this example, we define a rule named "Similar Job Title" for "People to People" type of recommendation. The Source and target field are jobTitle and their corresponding Field values are left empty and the type is Exact Match.
This will generate attendee recommendations for people who have similar job titles.
Example: Attendees having similar job titles will be recommended to each other.
This rule will generate session recommendations for people whose job title semantically matches with the session's description.
Example: An attendee with a job title Machine Learning Engineer will get recommendations of Sessions having descriptions related to Machine Learning. An example of such a session description is given below:
āIn this session our keynote speaker Mr. Dustin Porier who works as an AI Engineer in UFC will be explaining about the entire machine learning life cycle with its implementation using AWS Sagemakerā
This rule generate recommendations of people working in Nokia Company for Microsoft Employees and vice-versa.
Since the field value and target value text fields are populated with the company Nokia and Microsoft respectively, attendees who work in Nokia will be recommended to attendees working in Microsoft and vice versa.
This rule will generate session recommendations for people whose Interests field values match with the session tags.
Example: An attendee with Interest in Economics will get recommendations of Sessions having a tag Economics.
Target Field Value
Similar to Field Value, this can be used in situations where you want to recommend some specific source value to a specific target value. You can specify the target value in this text field.
Leave this text field empty if you want all possible target values to be used for comparison.