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Information Retrieval: Recent Advances and Beyond [PDF]

open access: yesIEEE Access, 2023
This paper provides an extensive and thorough overview of the models and techniques utilized in the first and second stages of the typical information retrieval processing chain.
Kailash A. Hambarde, Hugo Proença
semanticscholar   +1 more source

The Information Retrieval Experiment Platform [PDF]

open access: yesAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023
We integrate irdatasets, ir_measures, and PyTerrier with TIRA in the Information Retrieval Experiment Platform (TIREx) to promote more standardized, reproducible, scalable, and even blinded retrieval experiments.
Maik Frobe   +8 more
semanticscholar   +1 more source

COIL: Revisit Exact Lexical Match in Information Retrieval with Contextualized Inverted List [PDF]

open access: yesNorth American Chapter of the Association for Computational Linguistics, 2021
Classical information retrieval systems such as BM25 rely on exact lexical match and can carry out search efficiently with inverted list index. Recent neural IR models shifts towards soft matching all query document terms, but they lose the computation ...
Luyu Gao, Zhuyun Dai, Jamie Callan
semanticscholar   +1 more source

Study of Various Data Mining Methods to Select the Appropriate Method for Managers to Make Decisions in Urban Management (Case Study: Tehran Municipality) [PDF]

open access: yesعلوم و فنون مدیریت اطلاعات, 2021
Purpose: The main purpose of this article is to analyze the data of the Tehran Municipality websites and provide data mining solutions for managers' decisions.Methodology: This research is fundamental and in terms of nature, it can be considered ...
Shayesteh Shojaei Karizaki   +2 more
doaj   +1 more source

Neural Approaches to Conversational Information Retrieval [PDF]

open access: yesThe Information Retrieval Series, 2022
A conversational information retrieval (CIR) system is an information retrieval (IR) system with a conversational interface which allows users to interact with the system to seek information via multi-turn conversations of natural language, in spoken or ...
Jianfeng Gao   +3 more
semanticscholar   +1 more source

Using Deep-Learned Vector Representations for Page Stream Segmentation by Agglomerative Clustering

open access: yesAlgorithms, 2023
Page stream segmentation (PSS) is the task of retrieving the boundaries that separate source documents given a consecutive stream of documents (for example, sequentially scanned PDF files).
Lukas Busch   +2 more
doaj   +1 more source

UCN-YOLOv5: Traffic Sign Object Detection Algorithm Based on Deep Learning

open access: yesIEEE Access, 2023
Traffic sign detection plays an important role in traffic safety and traffic management. In view of the complex and changeable environment and detection accuracy of traffic sign detection, this paper proposes UCN-YOLOv5 model based on the framework of ...
Peilin Liu, Zhaoyang Xie, Taijun Li
doaj   +1 more source

Pyserini: A Python Toolkit for Reproducible Information Retrieval Research with Sparse and Dense Representations

open access: yesAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021
Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations. It aims to provide effective, reproducible, and easy-to-use first-stage retrieval in a multi-stage ranking architecture.
Jimmy J. Lin   +6 more
semanticscholar   +1 more source

Twitter Self-Organization to the Edge of a Phase Transition: Discrete-Time Model and Effective Early Warning Signals in Phase Space

open access: yesComplexity, 2023
Many real-world systems of various origins are capable of self-organization to the edge of a phase transition, characterized by avalanche-like behavior. Therefore, it is important, by observing the behavior of early warning measures for dynamical series ...
Andrey Dmitriev   +3 more
doaj   +1 more source

Causal Factor Disentanglement for Few-Shot Domain Adaptation in Video Prediction

open access: yesEntropy, 2023
An important challenge in machine learning is performing with accuracy when few training samples are available from the target distribution. If a large number of training samples from a related distribution are available, transfer learning can be used to
Nathan Cornille   +3 more
doaj   +1 more source

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