Information Processing and Management: an International Journal

• This paper proposed a fine-grained citation count prediction task (FGCCP), which predicts in-text citation count from each structural function of a paper ...

Previous studies have confirmed that citation mention and location reveal different contributions of the cited articles, and that both are significant in scientific research evaluation. However, traditional citation count prediction ...

• We establish a general group event recommendation framework in EBSN.
• We ...

In event-based social networks (EBSN), group event recommendation has become an important task for groups to quickly find events that they are interested in. Existing methods on group event recommendation either consider just one type ...

• This paper establishes an economic intervention model of cognitive computing to evaluate the health of population health management innovation, track the ...

With the emergence of Delta strains in many regions of China, population health issues have aroused great concern in many industries. Therefore, it is necessary to intervene in population health management through a variety of means. ...

Support vector machine (SVM) is a fundamental machine learning algorithm, while the traditional SVMs have limitations for massive and ubiquitous class-imbalanced data in practice. To address this issue, we propose a novel cost ...

• Study of protocol-independent features for representing texts to figth against spam.

This study addresses the usage of different features to complement synset-based and bag-of-words representations of texts in the context of using classical ML approaches for spam filtering (Ferrara, 2019). Despite the existence of a ...

Passage ranking has attracted considerable attention due to its importance in information retrieval (IR) and question answering (QA). Prior works have shown that pre-trained language models (e.g. BERT) can improve ranking performance. ...

• We propose a hybrid ranking architecture for passage ranking, that effectively solves the problem that ranking models are easily bewildered by the ...

Automated legal text classification is a prominent research topic in the legal field. It lays the foundation for building an intelligent legal system. Current literature focuses on international legal texts, such as Chinese cases, ...

• We apply domain concepts to legal text classification based on PCA and RFs to demonstrate its powerful ability for legal text.

This paper presents an approach to measuring business sentiment based on textual data. Business sentiment has been measured by traditional surveys, which are costly and time-consuming to conduct. To address the issues, we take ...

• Abundant newspaper articles are utilized to nowcast a business sentiment index.

Social sensing has become an emerging and pervasive sensing paradigm to collect timely observations of the physical world from human sensors. In this paper, we study the problem of geolocating abnormal traffic events using social ...

• Study the problem of geolocating abnormal traffic events using social media data.

Due to the growth of technology, the expansion of communication infrastructure and crises of COVID-19 pandemic, e-learning and virtual education is expanding. One of the best ways to access and organize these information is indexing ...

• LVTIA is a new method for video lecture indexing using statistical features.
• ...

• Analyzed socio-economic impact: pre, during and post lockdown periods.
• ...

Starting from December 2019, the novel COVID-19 threatens human lives and economies across the world. It was a matter of grave concern for the governments of all the countries as the deadly virus started expanding its paws over ...

• We propose a semantic understanding method combining a multi-feature kernel sparse classifier with a decision rule model for mangrove growth

With the rapid development of remote sensing technology, using remote sensing technology is an important means to monitor the dynamic change of land cover and ecology. In view of the complexity of mangrove ecological monitoring in ...

• Business intelligence has a significant effect on marketing through organizational learning.

Business Intelligence involves the strategies and technologies employed by businesses for the data analysis of business information. This study investigates the impact of Business Intelligence on the Marketing with emphasis on ...

Chinese second generation of the Audio Video Coding Standard, known as the AVS2, competing with HEVC/H.265 and AV1, has become a well-known video compression standard. Many unique tools have been developed and incorporated in AVS2. ...

• A frame level QP and λ allocation named reference structure determined parameter (RSDP) algorithm is proposed to satisfy GoP length 4, 8, and 16 ...

• The paper proposes a multi-source information fusion identification method based on VMD and SVM.

In order to solve the problem of the low leakage recognition rate of water pipes due to operating conditions influence in practice, a multi-source information fusion recognition method based on VMD and SVM is proposed. In this method, ...

• Identify the endorsement strategies of the citizen science projects by text mining.

This paper applies text analytics to study how the orientation of an endorsement strategy affects the public's willingness to participate in citizen science projects. Using 850 citizen science projects with 1,243 endorsements from an ...

Like many web platforms, Facebook is under pressure to regulate misinformation. According to the company, users that repeatedly share misinformation (‘repeat offenders’) will have their distribution reduced, but little is known about ...

• This article proposes the BEJNet network structure which combines the main body and the edge of the object for better feature extraction. On the basis of the ...

Scene segmentation is a very challenging task where convolutional neural networks are used in this field and have achieved very good results. Current scene segmentation methods often ignore the internal consistency of the target object,...

Most research on influence maximization focuses on the network structure features of the diffusion process but lacks the consideration of multi-dimensional characteristics. This paper proposes the attributed influence maximization ...

• The research of the paper is an expansion of the application field of the informetrics on network text mining.

With the rapid development of internet, text data is becoming richer, but most part of them is unstructured. So compared to statistics data, the text data is more difficult to be utilized. How to apply the informetrics on financial ...

Event factuality prediction is the task of assessing the degree to which an event mentioned in a sentence has happened. However, existing methods usually stack encoders to make factuality predictions given the gold positions of anchor ...

• A more practical End-to-End setting for Event Factuality Prediction is proposed.

As COVID-19 swept over the world, people discussed facts, expressed opinions, and shared sentiments about the pandemic on social media. Since policies such as travel restriction and lockdown in reaction to COVID-19 were made at ...

• A large-scale geo-tagged COVID-19 tweet dataset in the United States was released.

Open data is becoming ubiquitous as governments, companies, and even individuals have the option to offer more or less unrestricted access to their non-sensitive data. The benefits of open data, such as accessibility and transparency, ...

• This paper proposes a multi-lens framework with open data for modeling emerging events.

Emerging topic detection has attracted considerable attention in recent times. While various detection approaches have been proposed in this field, designing a method for accurately detecting emerging topics remains challenging. This ...

• Proposes a deep learning recommendation model which integrates textual review sentiments and rating matrix.

The matrix factorization model based on user-item rating data has been widely studied and applied in recommender systems. However, data sparsity, the cold-start problem, and poor explainability have restricted its performance. Textual ...

With the advent of the era of “we media,” many people's opinions have become easily accessible. Public health emergencies have always been an important aspect of public opinion exchange and emotional communication. In view of this ...

• We use a real-world customer service log, which contains three kinds of conversations: human-human conversation, human-AI conversation, human-human ...

Although there is an increasingly number of research about the design and use of conversational agents, it is still difficult for conversational agents to completely replace human service. Therefore, more and more companies have ...

Three-way opinion classification (3WOC) models are based on a human perspective of opinion classification and offer human-like decision-making capabilities. The purpose of this study was to determine the effectiveness of a three-way ...

• In opinion classification, judgements are based on relevance.
• We handle the ...

• Propose an anomaly detection classification model that incorporates federated learning and mixed Gaussian variational self-coding networks.

Anomalous data are such data that deviate from a large number of normal data points, which often have negative impacts on various systems. Current anomaly detection technology suffers from low detection accuracy, high false alarm rate ...