Legal case retrieval is a special Information Retrieval (IR) task focusi...
The research field of Information Retrieval (IR) has evolved significant...
Passage retrieval is a fundamental task in many information systems, suc...
Ranking systems are the key components of modern Information Retrieval (...
Ranking is at the core of many artificial intelligence (AI) applications...
The goal of unbiased learning to rank (ULTR) is to leverage implicit use...
This paper describes the approach of the THUIR team at the COLIEE 2023 L...
Legal case retrieval techniques play an essential role in modern intelli...
Legal case retrieval is a critical process for modern legal information
...
This paper introduces the approaches we have used to participate in the ...
Recent studies have shown that Dense Retrieval (DR) techniques can
signi...
Legal case retrieval, which aims to find relevant cases for a query case...
Ranking is at the core of Information Retrieval.
Classic ranking optim...
Existing conversational search studies mainly focused on asking better
c...
Conversational search has seen increased recent attention in both the IR...
This paper describes the approach of the THUIR team at the WSDM Cup 2023...
A long-standing challenge for search and conversational assistants is qu...
In last decades, legal case search has received more and more attention....
Recently substantial improvements in neural retrieval methods also bring...
Ranking systems are ubiquitous in modern Internet services, including on...
Neural ranking models (NRMs) have become one of the most important techn...
Ranking lies at the core of many Information Retrieval (IR) tasks. While...
Recent advance in Dense Retrieval (DR) techniques has significantly impr...
Unbiased Learning to Rank (ULTR) that learns to rank documents with bias...
State-of-the-art recommender system (RS) mostly rely on complex deep neu...
Result ranking often affects customer satisfaction as well as the amount...
In conversational search, agents can interact with users by asking clari...
Product retrieval systems have served as the main entry for customers to...
Learning to rank systems has become an important aspect of our daily lif...
Users often need to look through multiple search result pages or reformu...
Modern E-commerce websites contain heterogeneous sources of information,...
Traditional statistical retrieval models often treat each document as a
...
Rankings, especially those in search and recommendation systems, often
d...
User and item reviews are valuable for the construction of recommender
s...
Users often formulate their search queries with immature language withou...
Using reviews to learn user and item representations is important for
re...
In recent years, text-aware collaborative filtering methods have been
pr...
Leveraging biased click data for optimizing learning to rank systems has...
Different from shopping at retail stores, consumers on e-commerce platfo...
Product search is an important way for people to browse and purchase ite...
How to obtain an unbiased ranking model by learning to rank with biased ...
In product search, customers make purchase decisions based on not only t...
In learning-to-rank for information retrieval, a ranking model is
automa...
Product search is one of the most popular methods for customers to disco...
Intelligent assistants change the way people interact with computers and...
Product search is one of the most popular methods for people to discover...
Ranking models lie at the heart of research on information retrieval (IR...
Relevance feedback techniques assume that users provide relevance judgme...
As more and more search traffic comes from mobile phones, intelligent
as...
While in a classification or a regression setting a label or a value is
...