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Found 10 papers, 0 papers with code
Knowledge Graph-based Session Recommendation with Adaptive Propagation
Then, we adaptively aggregate items' neighbor information considering user intention within the learned session.
Hierarchical Multi-Task Learning Framework for Session-based Recommendations
However, the H-MTL framework has not been investigated in SBRSs yet.
M2TRec: Metadata-aware Multi-task Transformer for Large-scale and Cold-start free Session-based Recommendations
Using one public and one large industrial dataset, we experimentally show that state-of-the-art SBRSs have low performance on sparse sessions with sparse items.
Building chatbots from large scale domain-specific knowledge bases: challenges and opportunities
Popular conversational agents frameworks such as Alexa Skills Kit (ASK) and Google Actions (gActions) offer unprecedented opportunities for facilitating the development and deployment of voice-enabled AI solutions in various verticals.
Beyond Word Embeddings: Learning Entity and Concept Representations from Large Scale Knowledge Bases
We evaluate our concept embedding models on two tasks: (1) analogical reasoning, where we achieve a state-of-the-art performance of 91% on semantic analogies, (2) concept categorization, where we achieve a state-of-the-art performance on two benchmark datasets achieving categorization accuracy of 100% on one and 98% on the other.
Learning Concept Embeddings for Efficient Bag-of-Concepts Densification
Once they are learned, we propose an efficient vector aggregation method to generate fully continuous BoC representations.
Solving Cold-Start Problem in Large-scale Recommendation Engines: A Deep Learning Approach
One of the most important features of the proposed technique is the fact that it can be applied on top of any existing CF based recommendation engine without changing the CF core.
Entity Type Recognition using an Ensemble of Distributional Semantic Models to Enhance Query Understanding
The data set contains entities extracted from millions of job seekers/recruiters search queries, job postings, and resume documents.
Mined Semantic Analysis: A New Concept Space Model for Semantic Representation of Textual Data
The study positions MSA as one of state-of-the-art methods for measuring semantic relatedness, besides the inherent interpretability and simplicity of the generated semantic representation.
Watsonsim: Overview of a Question Answering Engine
The objective of the project is to design and run a system similar to Watson, designed to answer Jeopardy questions.
