Multimedia Information Retrieval

Raieli, Roberto

doi:10.1533/9781780633886

Cited by 9 publications

(6 citation statements)

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“…This estimation is based on the fact that whether the information collected can be transformed into outcomes is the main factor affecting the scale of difficulty reduced but not the only factor. Factors such as the form of the information collected [38], the amount of the information collected [2], and the obscurity of the information collected [39] will also slightly affect the scale of difficulty reduced. Based on [27], it is a feasible approach to model the reduction on difficulty caused by a main factor combined with many other factors as a variable that follows normal distribution.…”

Section: Modeling the Reduction Of Difficulty Caus-ed By The Informat...mentioning

confidence: 99%

A Probabilistic Model Toward How People Search to Build Outcomes

et al. 2023

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Although increased attention is being given to understanding how people search to build task outcomes, a formal model of the relation between how people search and how people build task outcomes is still lacking. This paper proposes a unified probabilistic model of how people search to build outcomes. The model involves 3 types of searcher behaviors (i.e., query submission, document selection, and information transformation) to model the effect of the information collected during search, and uses the item response theory to capture the ternary relations between the ability to transform information, the information collected, and the probability of successfully building task outcomes. We evaluate the proposed model in the task of identifying searchers' proficiencies under the assumption that high proficiency searchers would have high abilities to transform information. The results obtained high accuracies and F1 scores, which could reflect the effectiveness of the proposed model. The model contributes to the formal understanding of how people search to build task outcomes, and provides new possibilities for personalized and session-based information retrieval research.INDEX TERMS Item response theory, searching as learning, outcomes.

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Section: Modeling the Reduction Of Difficulty Caus-ed By The Informat...mentioning

confidence: 99%

A Probabilistic Model Toward How People Search to Build Outcomes

et al. 2023

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“…They further review LOD in digital libraries and discuss the current LOD research topics, including data and schema integration and distributed data management. Raieli (2016) argues that multimedia information retrieval offers a better information searching way because it is composed of content-based and semantic information retrieval methodologies. Zapounidou et al (2017) propose to study the representation of monographs, content relationships and whole-part relationships between them for enabling semantically richer interoperability.…”

Section: Recent Studies On Information Integration In Librariesmentioning

confidence: 99%

Information integration in libraries

Chen

2020

LHT

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PurposeThis paper investigates the latest achievements of studies on industrial information integration engineering (IIIE).Design/methodology/approachThis paper extends the research by Chen (2016) by reviewing studies from 2016 to 2019 in IEEE Xplore and Web of Science. Altogether, 970 papers related to IIIE are grouped into 27 research categories and reviewed.FindingsThe results obtained in this study indicate that the number of research studies on IIIE rose drastically in the past three years compared with the findings in Chen (2016). Particularly, energy, engineering, industrial control, information and communications technologies, instrumentation, manufacturing and transportation are the hot topics. This change proves that the Internet of things (IoT) and IIIE have integrated closely by providing more applications, such as industrial Internet of things (IIoT), cyber-physical system (CPS), smart grids and smart manufacturing. This change also proves the research direction of IIIE identified by Chen (2016).Originality/valueThe results present up-to-date development of IIIE and provide directions for future research on IIIE. The review identifies that energy, engineering, industrial control, information and communications technologies, instrumentation, manufacturing and transportation are the main fields that most of the reviewed papers focus on. Applications that integrate IoT and IIIE, including IIoT, CPS, smart grids and smart manufacturing, are attracting scholars' and practitioners' attention. Some new technologies, such as 5G and blockchain, have the potential to be integrated with IoT and IIIE.

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“…IR is applied in many areas and no course in IR is able to cover all the field's many applications. Having said so, there is a considerable amount of attention, both in textbooks and in surveys and tutorials for entity search [7,9], multimedia IR [65], product search [66], sponsored search [72], vertical search [5], and, obviously, web search, which is fully covered in all textbooks considered and extensively by Baeza-Yates and Ribeiro-Neto [6] and Manning et al [56]. Retrieval of semi-structured documents, e.g., XML retrieval, supported by the community's longstanding interest in document structure and by a range of community-based evaluation efforts related to semistructured documents [51], is covered in a relatively large number of today's textbooks.…”

Section: Applicationsmentioning

confidence: 99%

What Should We Teach in Information Retrieval?

Markov¹,

Rijke

2019

SIGIR Forum

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Modern Information Retrieval (IR) systems, such as search engines, recommender systems, and conversational agents, are best thought of as interactive systems. And their development is best thought of as a two-stage development process: offline development followed by continued online adaptation and development based on interactions with users. In this opinion paper, we take a closer look at existing IR textbooks and teaching materials, and examine to which degree they cover the offline and online stages of the IR system development process. We notice that current teaching materials in IR focus mostly on search and on the offline development phase. Other scenarios of interacting with information are largely absent from current IR teaching materials, as is the (interactive) online development phase. We identify a list of scenarios and a list of topics that we believe are essential to any modern set of IR teaching materials that claims to fully cover IR system development. In particular, we argue for more attention, in basic IR teaching materials, to scenarios such as recommender systems, and to topics such as query and interaction mining and understanding, online evaluation, and online learning to rank.

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Multimedia Information Retrieval

Cited by 9 publications

References 0 publications

A Probabilistic Model Toward How People Search to Build Outcomes

A Probabilistic Model Toward How People Search to Build Outcomes

Information integration in libraries

What Should We Teach in Information Retrieval?

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