Mitigating bias in algorithmic systems—a fish-eye view
Mitigating bias in algorithmic systems is a critical issue drawing attention across
communities within the information and computer sciences. Given the complexity of the …
communities within the information and computer sciences. Given the complexity of the …
An introduction to neural information retrieval
Neural ranking models for information retrieval (IR) use shallow or deep neural networks to
rank search results in response to a query. Traditional learning to rank models employ …
rank search results in response to a query. Traditional learning to rank models employ …
Neural models for information retrieval
Neural ranking models for information retrieval (IR) use shallow or deep neural networks to
rank search results in response to a query. Traditional learning to rank models employ …
rank search results in response to a query. Traditional learning to rank models employ …
A survey of query auto completion in information retrieval
In information retrieval, query auto completion (QAC), also known as typeahead [**ao et al.,
2013, Cai et al., 2014b] and auto-complete suggestion [Jain and Mishne, 2010], refers to the …
2013, Cai et al., 2014b] and auto-complete suggestion [Jain and Mishne, 2010], refers to the …
A proposed conceptual framework for a representational approach to information retrieval
J Lin - ACM SIGIR Forum, 2022 - dl.acm.org
This paper outlines a conceptual framework for understanding recent developments in
information retrieval and natural language processing that attempts to integrate dense and …
information retrieval and natural language processing that attempts to integrate dense and …
Comparing traditional and llm-based search for consumer choice: A randomized experiment
Recent advances in the development of large language models are rapidly changing how
online applications function. LLM-based search tools, for instance, offer a natural language …
online applications function. LLM-based search tools, for instance, offer a natural language …
Analyzing and learning from user interactions for search clarification
Asking clarifying questions in response to search queries has been recognized as a useful
technique for revealing the underlying intent of the query. Clarification has applications in …
technique for revealing the underlying intent of the query. Clarification has applications in …
Customized query auto-completion and suggestion—A review
Nowadays, with the widespread use of the internet, users meet their information needs with
the help of search engines. Users tend to retrieve the most relevant results by entering short …
the help of search engines. Users tend to retrieve the most relevant results by entering short …
A relative information gain-based query performance prediction framework with generated query variants
Query performance prediction (QPP) methods, which aim to predict the performance of a
query, often rely on evidences in the form of different characteristic patterns in the …
query, often rely on evidences in the form of different characteristic patterns in the …
Search interface design and evaluation
This monograph reviews research on the design and evaluation of search user interfaces
that has been published within the past 10 years. Our primary goal is to integrate state-of-the …
that has been published within the past 10 years. Our primary goal is to integrate state-of-the …