A General Approach to Multimodal Document Quality Assessment

Shen, Aili; Salehi, Bahar; Qi, Jianzhong; Baldwin, Timothy

doi:10.1613/jair.1.11647

Cited by 10 publications

(4 citation statements)

References 51 publications

(73 reference statements)

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“…We know that the body paragraphs take up the most words in a paper. (3) The results of removing the paper encoder show that the paper encoder also has a vital role in the model. It can do interaction among the title, abstract sentences, and body paragraphs.…”

Section: Ablation Studymentioning

confidence: 99%

A Modular Hierarchical Model for Paper Quality Evaluation

Deng¹,

Li²,

Yu³

et al. 2023

Artificial Intelligence Advances

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Paper quality evaluation is of great significance as it helps to select high quality papers from the massive amount of academic papers. However, existing models needs improvement on the interaction and aggregation of the hierarchical structure. These models also ignore the guiding role of the title and abstract in the paper text. To address above two issues, we propose a well-designed modular hierarchical model (MHM) for paper quality evaluation. Firstly, the input to our model is most of the paper text, and no additional information is needed. Secondly, we fully exploit the inherent hierarchy of the text with three encoders with attention mechanisms: a word-to-sentence(WtoS) encoder, a sentence-to-paragraph(StoP) encoder, and a paper encoder. Specifically, the WtoS encoder uses the pre-trained language model SciBERT to obtain the sentence representation from the word representation. The StoP encoder lets sentences in the same paragraph interact and aggregates them to get paragraph embeddings based on importance scores. The paper encoder does interaction among different hierarchical structures of three modules of a paper text: the paper title, abstract sentences, and body paragraphs. Then this encoder aggregates new representations generated into a compact vector. In addition, the paper encoder models the guiding role of the title and abstract, respectively, generating another two compact vectors. We concatenate the above three compact vectors and additional four manual features to obtain the paper representation. This representation is then fed into a classifier to obtain the acceptance decision, which is a proxy for papersÃ¢â‚¬â„¢ quality. Experimental results on a large-scale dataset built by ourselves show that our model consistently outperforms the previous strong baselines in four evaluation metrics. Quantitative and qualitative analyses further validate the superiority of our model.

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Section: Ablation Studymentioning

confidence: 99%

A Modular Hierarchical Model for Paper Quality Evaluation

Deng¹,

Li²,

Yu³

et al. 2023

Artificial Intelligence Advances

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show abstract

“…For document quality, Moustakis et al [44] summarize nine composite criteria that correspond to quality assessment including usefulness, reliability, animation, specialization, etc. Several works also incorporate evidence from structure information [62], gaze behaviour [42], inherent visual features [53,60] to assess document quality.…”

Section: Related Work 81 User Satisfaction In Web Searchmentioning

confidence: 99%

Pre-trained Language Model for Web-scale Retrieval in Baidu Search

Liu

Cheng

et al. 2021

Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &Amp; Data Mining

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Search engine plays a crucial role in satisfying users' diverse information needs. Recently, Pretrained Language Models (PLMs) based text ranking models have achieved huge success in web search. However, many state-of-the-art text ranking approaches only focus on core relevance while ignoring other dimensions that contribute to user satisfaction, e.g., document quality, recency, authority, etc. In this work, we focus on ranking user satisfaction rather than relevance in web search, and propose a PLM-based framework, namely SAT-Ranker, which comprehensively models different dimensions of user satisfaction in a unified manner. In particular, we leverage the capacities of PLMs on both textual and numerical inputs, and apply a multi-field input that modularizes each dimension of user satisfaction as an input field. Overall, SAT-Ranker is an effective, extensible, and data-centric framework that has huge potential for industrial applications. On rigorous offline and online experiments, SAT-Ranker obtains remarkable gains on various evaluation sets targeting different dimensions of user satisfaction. It is now fully deployed online to improve the usability of our search engine. CCS CONCEPTS• Information systems → Language models; Learning to rank.

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“…At present, when the level of consumer knowledge is increasing, consumers' demand for commodity information with the help of packaging is reflected in comprehensiveness, convenience, interactivity, fun, etc. To meet the changing needs of society [10][11][12], a new green concept product packaging system is necessary. A circular economy refers to a new and sustainable way of economic development to maximize the maximum environmental benefit.…”

Section: Introductionmentioning

confidence: 99%

Design and research of green concept product packaging based on artificial intelligence technology

Zhu

2023

Applied Mathematics and Nonlinear Sciences

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Through data mining, this paper completes collecting and mining information in the database using artificial intelligence. Secondly, the graphical method is analyzed, image normalization calculation is carried out to complete the technical support for green concept packaging design, and a green concept product packaging design system based on artificial intelligence technology is constructed. Finally, the ease of use experiment and user satisfaction test confirmed it. The user satisfaction test showed a satisfaction rate of 95% for response time and 97% for material recycling. The fact that other test options are above 90% indicates that the green concept product packaging design based on artificial intelligence technology is feasible.

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A General Approach to Multimodal Document Quality Assessment

Cited by 10 publications

References 51 publications

A Modular Hierarchical Model for Paper Quality Evaluation

A Modular Hierarchical Model for Paper Quality Evaluation

Pre-trained Language Model for Web-scale Retrieval in Baidu Search

Design and research of green concept product packaging based on artificial intelligence technology

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