Monday, January 20, 2020

Personalized Conversational Recommendation Systems :: Business Communications

Conversation via Dialogue Management Up: Personalized Conversational Recommendation Systems Conversational Recommendation The goal of recommendation systems is to help users find items of interest, and thus they must eliminate some choices from consideration while keeping others. To achieve this, they must either know or determine the interests of the current user, then present items that satisfy those interests. One of the most widely used approaches for information acquisition in recommendation systems is the use of a simple form (usually a single query box) that the user fills in. Coupled with this, a common presentation format is the ranked list approach. In this scheme, the system presents a usually long list of results, ordered by their predicted relevance to the user. The combined technique of information acquisition through a form and presentation in a list originated in information retrieval, where it was used to help find documents or reports during library research. The basic method, which we refer to as the ranked list approach, is more general, however, and it underlies the simpler search e ngines for the World Wide Web, which are used regularly for many different selection tasks. In contrast, the ADAPTIVE PLACE ADVISOR supports conversations as its mode of interaction. In this approach, one conversational participant, which we call the inquirer, asks a second participant, which we call the advisor, for assistance in selecting an item. For example, if the inquirer is deciding on a restaurant at which to have dinner, the conversation may proceed as follows: 1. Inquirer: Where do you think I should eat tonight? 2. Advisor: What type of food would you like? 3. Inquirer: What types are there? 4. Advisor: You can say things like Chinese, Indian, and Mediterranean. 5. Inquirer: Oh, maybe a cheap Indian place. 6. Advisor: What kind of parking would you like? 7. Inquirer: I don't care, as long as it's in Palo Alto. 8. Advisor: I'm sorry, I don't know of any restaurants like that, would you like to search for any price? 9. Inquirer: No, I think I'd like Chinese instead. 10. Advisor: How does Mandarin Gourmet on 420 Ramona sound?1 11. Inquirer: No, what else do you have? 12. Advisor: How about Jing-Jing Szechwan Hunan Gourmet on 443 Emerson Street? 13. Inquirer: Sure, that sounds fine. We will refer to systems that mimic this approach to recommendation as conversational recommendation systems. The interaction supported by conversational recommendation systems is quite different from that found in the ranked list approach.

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