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Problem Statement: The huge number of information on the web as well as the growth of new inexperienced users creates new challenges for information retrieval. It has become increasingly difficult for these users to find relevant documents…

Information Retrieval · Computer Science 2011-06-14 Abdelkrim Bouramoul , Mohamed-Khireddine Kholladi , Bich-Lien Doan

Nowadays, search engine users commonly rely on query suggestions to improve their initial inputs. Current systems are very good at recommending lexical adaptations or spelling corrections to users' queries. However, they often struggle to…

Information Retrieval · Computer Science 2023-01-24 Jorge Gabín , M. Eduardo Ares , Javier Parapar

Query expansion is a functionality of search engines that suggests a set of related queries for a user-issued keyword query. Typical corpus-driven keyword query expansion approaches return popular words in the results as expanded queries.…

Information Retrieval · Computer Science 2011-04-19 Ziyang Liu , Sivaramakrishnan Natarajan , Yi Chen

Recommenders take place on a wide scale of e-commerce systems, reducing the problem of information overload. The most common approach is to choose a recommender used by the system to make predictions. However, users vary from each other;…

Information Retrieval · Computer Science 2024-10-18 Peter Tibensky , Michal Kompan

Thinking of todays web search scenario which is mainly keyword based, leads to the need of effective and meaningful search provided by Semantic Web. Existing search engines are vulnerable to provide relevant answers to users query due to…

Information Retrieval · Computer Science 2013-11-26 Debajyoti Mukhopadhyay , Manoj Sharma , Gajanan Joshi , Trupti Pagare , Adarsha Palwe

Voice search is becoming a popular mode for interacting with search engines. As a result, research has gone into building better voice transcription engines, interfaces, and search engines that better handle inherent verbosity of queries.…

Information Retrieval · Computer Science 2013-12-17 Apoorv Narang , Srikanta Bedathur

Users who need several queries before finding what they need can benefit from an automatic search assistant that provides feedback on their query modification strategies. We present a method to learn from a search log which types of query…

Information Retrieval · Computer Science 2011-04-04 Vera Hollink , Arjen de Vries

Interactive query expansion can assist users during their query formulation process. We conducted a user study with over 4,000 unique visitors and four different design approaches for a search term suggestion service. As a basis for our…

Digital Libraries · Computer Science 2019-03-29 Daniel Hienert , Philipp Schaer , Johann Schaible , Philipp Mayr

In ecommerce search, query autocomplete plays a critical role to help users in their shopping journey. Often times, query autocomplete presents users with semantically similar queries, which can impede the user's ability to find diverse and…

Information Theory · Computer Science 2025-05-14 Adithya Rajan , Weiqi Tong , Greg Sharp , Prateek Verma , Kevin Li

This research aims to explore various methods for assessing user feedback in mixed-initiative conversational search (CS) systems. While CS systems enjoy profuse advancements across multiple aspects, recent research fails to successfully…

Information Retrieval · Computer Science 2023-05-09 Paul Owoicho , Ivan Sekulić , Mohammad Aliannejadi , Jeffrey Dalton , Fabio Crestani

Query recommendation systems are ubiquitous in modern search engines, assisting users in producing effective queries to meet their information needs. However, these systems require a large amount of data to produce good recommendations,…

Information Retrieval · Computer Science 2024-06-05 Andrea Bacciu , Enrico Palumbo , Andreas Damianou , Nicola Tonellotto , Fabrizio Silvestri

This paper presents a deployed, production-grade system designed to enhance and scale search query datasets for intent-based recommendation systems in digital banking. In real-world environments, the growing volume and complexity of user…

Information Retrieval · Computer Science 2025-08-25 Aaron Rodrigues , Mahmood Hegazy , Azzam Naeem

Despite their important role in online information search, search query suggestions have not been researched as much as most other aspects of search engines. Although reasons for this are multi-faceted, the sparseness of context and the…

Information Retrieval · Computer Science 2026-01-07 Fabian Haak , Philipp Schaer

Purpose - To test major Web search engines on their performance on navigational queries, i.e. searches for homepages. Design/methodology/approach - 100 real user queries are posed to six search engines (Google, Yahoo, MSN, Ask, Seekport,…

Information Retrieval · Computer Science 2015-11-19 Dirk Lewandowski

Information on the web is prodigious; searching relevant information is difficult making web users to rely on search engines for finding relevant information on the web. Search engines index and categorize web pages according to their…

Artificial Intelligence · Computer Science 2015-10-06 Jai Manral

Study shows that software developers spend about 19% of their time looking for information in the web during software development and maintenance. Traditional web search forces them to leave the working environment (e.g., IDE) and look for…

Software Engineering · Computer Science 2018-07-09 Mohammad Masudur Rahman , Shamima Yeasmin , Chanchal K. Roy

Due to the increasing storage data on Web Applications, it becomes very difficult to use only keyword-based searches to provide comprehensive search results, thus increasing the difficulty for web users to search information on the web. In…

Information Retrieval · Computer Science 2021-10-12 Ikechukwu Onyenwe , Stanley Ogbonna , Ebele Onyedimma , Onyedikachukwu Ikechukwu-Onyenwe , Chidinma Nwafor

Search is an integral part of a software development process. Developers often use search engines to look for information during development, including reusable code snippets, API understanding, and reference examples. Developers tend to…

Modern machine learning relies on datasets to develop and validate research ideas. Given the growth of publicly available data, finding the right dataset to use is increasingly difficult. Any research question imposes explicit and implicit…

Information Retrieval · Computer Science 2023-06-08 Vijay Viswanathan , Luyu Gao , Tongshuang Wu , Pengfei Liu , Graham Neubig

Large Language Models (LLMs) excel at tackling various natural language tasks. However, due to the significant costs involved in re-training or fine-tuning them, they remain largely static and difficult to personalize. Nevertheless, a…

Information Retrieval · Computer Science 2024-02-20 Jinheon Baek , Nirupama Chandrasekaran , Silviu Cucerzan , Allen herring , Sujay Kumar Jauhar