DeepAI AI Chat
Log In Sign Up

On Interpretation and Measurement of Soft Attributes for Recommendation

05/19/2021
by   Krisztian Balog, et al.
0

We address how to robustly interpret natural language refinements (or critiques) in recommender systems. In particular, in human-human recommendation settings people frequently use soft attributes to express preferences about items, including concepts like the originality of a movie plot, the noisiness of a venue, or the complexity of a recipe. While binary tagging is extensively studied in the context of recommender systems, soft attributes often involve subjective and contextual aspects, which cannot be captured reliably in this way, nor be represented as objective binary truth in a knowledge base. This also adds important considerations when measuring soft attribute ranking. We propose a more natural representation as personalized relative statements, rather than as absolute item properties. We present novel data collection techniques and evaluation approaches, and a new public dataset. We also propose a set of scoring approaches, from unsupervised to weakly supervised to fully supervised, as a step towards interpreting and acting upon soft attribute based critiques.

READ FULL TEXT

page 1

page 2

page 3

page 4

04/27/2020

Personalized Recommendation of PoIs to People with Autism

The suggestion of Points of Interest to people with Autism Spectrum Diso...
12/09/2021

Self-Supervised Bot Play for Conversational Recommendation with Justifications

Conversational recommender systems offer the promise of interactive, eng...
04/04/2022

CARCA: Context and Attribute-Aware Next-Item Recommendation via Cross-Attention

In sparse recommender settings, users' context and item attributes play ...
05/30/2019

Explainable Fashion Recommendation: A Semantic Attribute Region Guided Approach

In fashion recommender systems, each product usually consists of multipl...
04/20/2017

Using Mise-En-Scène Visual Features based on MPEG-7 and Deep Learning for Movie Recommendation

Item features play an important role in movie recommender systems, where...
05/28/2019

Constructing High Precision Knowledge Bases with Subjective and Factual Attributes

Knowledge bases (KBs) are the backbone of many ubiquitous applications a...