|
| | | | |
| | | |
| Stat |
Members: 3645
Articles: 2'501'711
Articles rated: 2609
20 April 2024 |
|
| | | | |
|
Article overview
| |
|
|
Towards Topic-Guided Conversational Recommender System | | Kun Zhou
; Yuanhang Zhou
; Wayne Xin Zhao
; Xiaoke Wang
; Ji-Rong Wen
; | | Date: |
8 Oct 2020 | | Abstract: | Conversational recommender systems (CRS) aim to recommend high-quality items
to users through interactive conversations. To develop an effective CRS, the
support of high-quality datasets is essential. Existing CRS datasets mainly
focus on immediate requests from users, while lack proactive guidance to the
recommendation scenario. In this paper, we contribute a new CRS dataset named
extbf{TG-ReDial} ( extbf{Re}commendation through
extbf{T}opic- extbf{G}uided extbf{Dial}og). Our dataset has two major
features. First, it incorporates topic threads to enforce natural semantic
transitions towards the recommendation scenario. Second, it is created in a
semi-automatic way, hence human annotation is more reasonable and controllable.
Based on TG-ReDial, we present the task of topic-guided conversational
recommendation, and propose an effective approach to this task. Extensive
experiments have demonstrated the effectiveness of our approach on three
sub-tasks, namely topic prediction, item recommendation and response
generation. TG-ReDial is available at this https URL | | Source: | arXiv, 2010.04125 | | Services: | Forum | Review | PDF | Favorites | |
|
|
No review found.
Did you like this article?
Note: answers to reviews or questions about the article must be posted in the forum section.
Authors are not allowed to review their own article. They can use the forum section.
browser Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)
|
| |
|
|
|
|
News, job offers and information for researchers and scientists:
| |
REGISTER