25 papers · ranked by Valyu relevance
Fábio Crestani, Stefano Mizzaro, Ivan Scagnetto
| 1 | | Introduction | 1 | | --- | --- | --- | --- | | | 1.1 | Information Retrieval with Mobile Devices | 1 | | | 1.2 | Motivations and Methodology | 2 | | | 1.3 | Outline | 3 | | 2 | | From IR to Mobile IR | 5 | | | 2.1 | Information Retrieval | 5 | | | | 2.1.1 Brief Introduction to Information Retrieval | 5 | | | |…
Wei Zhou, Neil R Smalheiser, Clement Yu
This informal tutorial is intended for investigators and students who would like to understand the workings of information retrieval systems, including the most frequently used search engines: PubMed and Google. Having a basic knowledge of the terms and concepts of information retrieval should improve the efficiency…
Farivar, Kayla
Information retrieval systems have progressed notably from lexical techniques such as BM25 and TF-IDF to modern semantic retrievers. This survey provides a brief overview of the BM25 baseline, then discusses the architecture of modern state-of-the-art semantic retrievers. Advancing from BERT, we introduce dense…
Maher Abdullah, Mohammed G.H. Al Zamil
Large amount of unstructured designed information is difficult to deal with. Obtaining specific information is a hard mission and takes a lot of time. Information Retrieval System (IR) is a way to solve this kind of problem. IR is a good mechanism but does not give the perfect solution. Other techniques have been added…
Santanu Acharjee, R. K. Choudhury
Due to the exponential growth of big data in this digital era, an advanced method for effective information retrieval becomes essential. The basic objective of this paper is to propose a topology-based method for cognitive information retrieval (CIR) in big data environments. By using concepts such as cognitive…
Paul Thompson, Juliette C. Madan, Jason H. Moore
Background Retrieving relevant biomedical literature has become increasingly difficult due to the large volume and rapid growth of biomedical publication. A query to a biomedical retrieval system often retrieves hundreds of results. Since the searcher will not likely consider all of these documents, ranking the…
V. R. Kanagavalli, G. Maheeja
This paper tries to throw light in the usage of data structures in the field of information retrieval. Information retrieval is an area of study which is gaining momentum as the need and urge for sharing and exploring information is growing day by day. Data structures have been the area of research for a long period in…
Mohameth-François Sy, Sylvie Ranwez, Jacky Montmain, Armelle Regnault + 2 more
'Armelle Regnault' 'Michel Crampes' 'Vincent Ranwez'] Background Because of the increasing number of electronic resources, designing efficient tools to retrieve and exploit them is a major challenge. Some improvements have been offered by semantic Web technologies and applications based on domain ontologies. In life…
Bilal Abu-Salih
Information Retrieval (IR) allows the storage, management, processing and retrieval of information, documents, websites, etc. Building an IR system for any language is imperative. This is evident through the massive conducted efforts to build IR systems using any of its models that are valid for certain languages. This…
Sohrab Ferdowsi, Nikolay Borissov, Elham Kashani, David Vicente Alvarez + 4 more
In the context of searching for COVID-19 related scientific literature, we present an information retrieval methodology for effectively finding relevant publications for different information needs. We discuss different components of our architecture consisting of traditional information retrieval models, as well as…
Michael Segundo Ortiz, Mengqian Wang, Kazuhiro Seki, Heejun Kim + 1 more
In this work we present Publication Access Through Tiered Interaction & Exploration (PATTIE) – an information foraging, sense-making, and exploratory spatial-semantic information retrieval (IR) system (http://pattie.unc.edu/plos). Non-spatial, spatial IR systems, and some recent studies focused on their principal…
Pranav Punuru, Nabil Ibtehaz, Swagarika Giri, Harsha Srirangam + 2 more
The rapid expansion of biomedical literature has made comprehensive manual synthesis increasingly difficult to perform effectively, creating a pressing need for AI systems capable of reasoning across verified evidence rather than merely retrieving it. However, existing retrieval-augmented generation (RAG) methods often…
Peter Bruza, Henderik A. Proper
We are surrounded by an ever increasing amount of data that is stored in a variety of databases. In this article we will use a very liberal definition of database. Basically any collection of data can be regarded as a database, ranging from the files in a directory on a disk, to ftp and web servers, through to…
Poluru Eswaraiah, Hussain Syed, Natalia Kryvinska
Multimedia data, which includes textual information, is employed in a variety of practical computer vision applications. More than a million new records are added to social media and news sites every day, and the text content they contain has gotten increasingly complex. Finding a meaningful text record in an archive…
Feng Wu, Yanting Ji, Wenping Shi
In today's society, people's lives are increasingly inseparable from computer information. Due to the continuous improvement of technology and the rapid development of internet technology, the network environment is becoming more and more complex, which makes it easy to cause loopholes in the information retrieval…
Ian Soboroff
1## Introduction The Text Retrieval Conference (TREC) is a community evaluation and dataset construction activity sponsored by the U.S. National Institute of Standards and Technology (NIST). TREC has run annually since 1991. TREC is divided into tracks which embody specific search tasks. The canonical TREC task is…
Authors not listed
Large language models (LLMs) have garnered increasing attention owing to their potential as collaborative assistants in scientific studies. However, adapting an LLM to specialized domains remains challenging because of the difficulty in incorporating domain-specific knowledge. In the present study, we propose a…
Authors not listed
Bayesian optimization (BO) has become increasingly important for experimental optimization across scientific domains, yet implementing BO pipelines requires significant programming expertise and familiarity with specialized frameworks. This creates a barrier for domain experts who could benefit from BO but lack the…
Authors not listed
In recent years, the development of large language models (LLMs) has revolutionized various fields of natural science, yet their application in molecular data processing remains constrained due to the reliance on single-modality inputs and outputs. To bridge the gap between experimenters and computational tools, we…
Alexander M. Waldrop, John B. Cheadle, Kira Bradford, Alexander Preiss + 14 more
As the number of public data resources continues to proliferate, identifying relevant datasets across heterogenous repositories is becoming critical to answering scientific questions. To help researchers navigate this data landscape, we developed Dug: a semantic search tool for biomedical datasets utilizing…
Authors not listed
The interdisciplinary nature of redox flow batteries (RFBs), spanning chemistry, materials, and engineering, has led to a vast and fragmented body of research, hindering the efficient synthesis of knowledge. An intelligent question-answering system is there-fore essential to organize this dispersed knowledge, enhance…
Bohdan B. Khomtchouk, Kasra A. Vand, Thor Wahlestedt, Kelly Khomtchouk + 2 more
We propose a search engine and file retrieval system for all bioinformatics databases worldwide. PubData searches biomedical data in a user-friendly fashion similar to how PubMed searches biomedical literature. PubData is built on novel network programming, natural language processing, and artificial intelligence…
Authors not listed
The materials-science literature is the richest reservoir of domain knowledge, yet converting its unstructured text—especially narrative passages and complex tables—into machine-readable data for analysis and ML model training remains challenging. To address this, we present KnowMat, an agentic, multi-stage pipeline…
Haohan Wang, Xiang Liu, Yifeng Tao, Wenting Ye + 3 more
The increasing amount of scientific literature in biological and biomedical science research has created a challenge in the continuous and reliable curation of the latest knowledge discovered, and automatic biomedical text-mining has been one of the answers to this chal-lenge. In this paper, we aim to further improve…
Charlotte Neidiger, Tarek Saier, Kai Kühn, Victor Larignon + 12 more
In this work, a concept for an open chemistry knowledge base was developed to integrate chemical research results into a collaboratively usable platform. To achieve this, we enhanced Semantic MediaWiki (SMW) to support the collection and structured summary of chemical data contained in publications. We implemented…