The increase in popularity for Artificial Intelligence has opened the door for a new era of industrial revolution. One of the most prevalent problems today is utilizing data to generate useful insights for decision making.

This paper introduces a prospective data modeling and a dataset of conversation messages collected via our self-developed chatbot on Facebook. The chatbot, Her/Her act as an agent for matching pairs of female users to chat anonymously with all messages relayed by the chatbot to keep both users' identities confidential. The dataset consists of more than 60,000 female users and millions of Traditional Chinese conversational messages.

This paper introduces the use of shortest Euclidean distance and classification modeling as the optimization tools for enhancing matchi...[ Read more ]

The increase in popularity for Artificial Intelligence has opened the door for a new era of industrial revolution. One of the most prevalent problems today is utilizing data to generate useful insights for decision making.

This paper introduces a prospective data modeling and a dataset of conversation messages collected via our self-developed chatbot on Facebook. The chatbot, Her/Her act as an agent for matching pairs of female users to chat anonymously with all messages relayed by the chatbot to keep both users' identities confidential. The dataset consists of more than 60,000 female users and millions of Traditional Chinese conversational messages.

This paper introduces the use of shortest Euclidean distance and classification modeling as the optimization tools for enhancing matching quality. Using these techniques, the matching performance are better than original random matching. This paper also documented the market potential of such online matching platform being a social venture as well.

Keywords: Machine Learning, Conversational text, Matching, Business Intelligence, Homosexual Business, Social Venture