Recommender systems (RS) have achieved significant success by leveraging...
A typical benchmark dataset for recommender system (RecSys) evaluation
c...
Fast-growing scientific publications present challenges to the scientifi...
Goal-oriented Script Generation is a new task of generating a list of st...
Open Information Extraction (OIE) aims to extract factual relational tup...
In a practical recommender system, new interactions are continuously
obs...
Open Information Extraction (OIE) aims to extract relational tuples from...
Few-shot event detection (ED) has been widely studied, while this brings...
Mainstream solutions to Sequential Recommendation (SR) represent items w...
Given comparative text, comparative relation extraction aims to extract ...
Large Language Models (LLMs) have made remarkable strides in various tas...
Deep learning technologies have brought us many models that outperform h...
Open Information Extraction (OpenIE) aims to extract relational tuples f...
Recently, amounts of works utilize perplexity (PPL) to evaluate the qual...
Recently, a few papers report counter-intuitive observations made from
e...
Multi-scenario learning (MSL) enables a service provider to cater for us...
Open Information Extraction (OpenIE) facilitates domain-independent disc...
In academic research, recommender systems are often evaluated on benchma...
Many studies on dialog emotion analysis focus on utterance-level emotion...
A sentence may express sentiments on multiple aspects. When these aspect...
Conducting a systematic review (SR) is comprised of multiple tasks: (i)
...
When medical researchers conduct a systematic review (SR), screening stu...
Sarcasm employs ambivalence, where one says something positive but actua...
Collaborative filtering (CF) is widely used to learn an informative late...
Open Information Extraction (OpenIE) aims to extract structured relation...
Recent advances in reinforcement learning have inspired increasing inter...
Deep reinforcement learning enables an agent to capture user's interest
...
In academic research, recommender models are often evaluated offline on
...
Popularity is often included in experimental evaluation to provide a
ref...
In a large recommender system, the products (or items) could be in many
...
Corporations today face increasing demands for the timely and effective
...
In this paper, we define and study a new task called Context-Aware Seman...
As a dual problem of influence maximization, the seed minimization probl...
Cloze-style reading comprehension in Chinese is still limited due to the...
Deep learning based recommender systems have been extensively explored i...
Targeted sentiment analysis (TSA), also known as aspect based sentiment
...
In evidence-based medicine, relevance of medical literature is determine...
In biomedical area, medical concepts linked to external knowledge bases
...
Named entity recognition (NER) is the task to identify text spans that
m...
In this paper, we propose a novel sequence-aware recommendation model. O...
Predicting the missing values given the observed interaction matrix is a...
Modelling user-item interaction patterns is an important task for
person...
Collective entity disambiguation, or collective entity linking aims to
j...