ChengXiang Zhai

Retrieval of Relevant Opinion Sentences for New Products

2015

With the rapid development of Internet and E-commerce, abundant product reviews have been written by consumers who bought the products. These reviews are very useful for consumers to optimize their purchasing decisions. However, since the …

A Study of Smoothing Methods for Language Models Applied to Ad Hoc Information Retrieval

2017 · ACM SIGIR Forum

Language modeling approaches to information retrieval are attractive and promising because they connect the problem of retrieval with that of language model estimation, which has been studied extensively in other application areas such as speech …

Are we on the Right Track?

2018

The unpredictability of user behavior and the need for effectiveness make it difficult to define a suitable research methodology for Information Retrieval (IR). In order to tackle this challenge, we categorize existing IR methodologies along …

Adapting Sequence to Sequence Models for Text Normalization in Social Media

2019 · Proceedings of the International AAAI Conference on Web and Social Media

Social media offer an abundant source of valuable raw data, however informal writing can quickly become a bottleneck for many natural language processing (NLP) tasks. Off-theshelf tools are usually trained on formal text and cannot …

Interactive Information Retrieval: Models, Algorithms, and Evaluation

2020

Since Information Retrieval (IR) is an interactive process in general, it is important to study Interactive Information Retrieval (IIR), where we would attempt to model and optimize an entire interactive retrieval process (rather than a …

oBERTa: Improving Sparse Transfer Learning via improved initialization, distillation, and pruning regimes

2023 · arXiv (Cornell University)

In this paper, we introduce the range of oBERTa language models, an easy-to-use set of language models which allows Natural Language Processing (NLP) practitioners to obtain between 3.8 and 24.3 times faster models without expertise …

TextData: Save What You Know and Find What You Don't

2024

In this demonstration, we present TextData, a novel online system that enables users to both "save what they know" and "find what they don't". TextData was developed based on the Community Digital Library (CDL) system. …

Document Language Models, Query Models, and Risk Minimization for Information Retrieval

2017 · ACM SIGIR Forum

We present a framework for information retrieval that combines document models and query models using a probabilistic ranking function based on Bayesian decision theory. The framework suggests an operational retrieval model that extends recent developments …

Neural-Answering Logical Queries on Knowledge Graphs

2021

Logical queries constitute an important subset of questions posed in knowledge graph question answering systems. Yet, effectively answering logical queries on large knowledge graphs remains a highly challenging problem. Traditional subgraph matching based methods might …