Expert Systems with Applications: An International Journal

• Query expansion based on term distribution is better than Pseudo Relevance Feedback.

Query Expansion (QE) approaches that involve the reformulation of queries by adding new terms to the initial user query, are intended to ameliorate the vocabulary mismatch between the query keywords and the documents’ in Information ...

• Combining pre-trained language model and GNN for few-shot text classification.
• ...

Few-shot text classification aims to learn a classifier from very few labeled text instances per class. Previous few-shot research works in NLP are mainly based on Prototypical Networks, which encode support set samples of each class ...

• Address the domain shift problem with a limited amount of available datasets.
• ...

The capability of generalization to unseen domains is crucial for deep learning models when considering real-world scenarios. However, current available medical image datasets, such as those for COVID-19 CT images, have large ...

• In-vehicle sensor data are useful to identify unsafe driving behavior.
• A feed-...

Traffic crashes are one of the biggest causes of accidental death in the way where, every year, more than 1.35 million of people die. In most of them, the main cause is related to the driver’s behavior. The driver performs a set of ...

• More flexible controller tuning is achieved combining DMPC and fuzzy approaches.

This work presents a hierarchical distributed model predictive control approach for multiple agents with cooperative negotiations based on fuzzy inference. Specifically, a fuzzy-based two-layer control architecture is proposed. In the ...

• Adapting methods to explore attributes’ influence and detect objects’ siblings.

Nowadays, firms are strongly racing to raise their competitive level in the international market. As this market has a natural connection, therefore, one of the vital roads for competing is exploring the users’ behaviour which ...

• CLAFMM, to alter the class label depending on a secondary training set, is proposed.

Hyperbox classifier is efficiently implemented using fuzzy min max neural network, where the input patterns present in the training phase place a vital role. In the training phase, a set of hyperboxes are constructed which are used to ...

• Classification of features into comment and sentence specific.
• Better Results ...

Bug report is one of the major software artifact which is generated during the software development process. Changing requirements in the software development process leads to the continuous evolution of bugs which give challenges to ...

• A novel hybrid ensemble model for default prediction is proposed.
• LightGBM is ...

Default prediction plays an important role in emerging financial market, so it has attracted extensive attention from financial industry and academic community. A slight improvement in default prediction performance can avoid huge ...

• Conceived a context-independent Collaboration recommendation system for inventors.

Precise and timely information about opportunities for potential collaborations is very vital for the collaboration-intense research environment prevailing in innovation ecosystems. As the identification of suitable inventors for ...

• A deep learning COVID-19 diagnostic system is developed using state-of-the-art deep learning architectures.

In recent months, a novel virus named Coronavirus has emerged to become a pandemic. The virus is spreading not only humans, but it is also affecting animals. First ever case of Coronavirus was registered in city of Wuhan, Hubei ...

• A novel framework for prioritizing equipment toward life extension;
• Combining ...

Many machine learning algorithms and models have been proposed in the literature for predicting the remaining useful life (RUL) of systems and components that are subject to condition monitoring (CM). However, in cases where data is ...

• A novel method (GcForest-PPI) to predict protein–protein interactions.
• The ...

Prediction of protein–protein interactions (PPIs) helps to grasp molecular roots of disease. However, web-lab experiments to predict PPIs are limited and costly. Using machine-learning-based frameworks can not only automatically ...

• Every growing data volume also incorporate extraordinary dimensions.
• Hybrid ...

Feature selection, an optimization problem, becomes an important pre-process tool in data mining, which simultaneously aims at minimizing feature-size and maximizing model generalization. Because of large search space, conventional ...

• Edge preserving optimal guided filtering-based image denoising is proposed.
• ...

In this work, a novel and efficient approach for image denoising is proposed. More often, noise affecting the pixels in image is Gaussian in nature and uniformly deters information pixels in image irrespective of their intensity ...

• Applies a dynamic bit-vector data structure using an electromagnetic field approach.

Hiding the association rules is one of the methods used to protect sensitive information in data-mining processes. Its goal is to transform the original dataset so that the support for, or the reliability of, sensitive rules is reduced ...

• Four new models for Traveling Repairman Problem with time windows are developed.

The Traveling Repairman Problem (TRP) is one of the most important variants of the Traveling Salesman Problem (TSP). The objective function of TRP is to find a Hamiltonian path or tour starting from the origin while minimizing the ...

• Classification methods are presented for image classification into road and non-road.

Road networks are one of the main urban features. Therefore, road parts extraction from high-resolution remotely sensed imagery and updated road database are beneficial for many GIS applications. However, owing to the presence of ...

• In evolutionary clustering, the goal is to find a series of clustering results over time.

K-Means algorithm is probably the most famous and popular clustering algorithm in the world. K-Means algorithm has the advantages of simple structure, easy implementation, high efficiency, fast convergence speed, and good results. It ...

• First, NOC_SET standard data set is constructed.
• Second, some flow features are ...

With the current massive amount of traffic that is going through the internet, internet service providers (ISPs) and networking service providers (NSPs) are looking for various ways to accurately predict the application type of flow ...

• Developed a global optimization approach using cooperative meta-heuristic methods.

This paper presents an alternative global optimization meta-heuristics (MHs) approach, inspired by the natural selection theory. The proposed approach depends on the competition among six MHs that allows generating an offspring, which ...

• We propose a novel approach to jointly explore labeled and unlabeled samples.
• ...

In the past few years, Safe Semi-Supervised Learning (S3L) has become an emerging research topic. A few studies have been investigated in the S3L field and obtained desired performance. However, these studies mainly focus on ...

• Proposing a new hybrid improved Whale Optimization Salp Swarm Algorithm (IWOSSA).

In this paper, a hybrid improved whale optimization salp swarm algorithm (IWOSSA) is proposed. The main idea behind IWOSSA is to combine improved Whale Optimization Algorithm (IWOA) and Salp Swarm Algorithm (SSA). First, WOA algorithm ...

• We propose an agent-based model to analyze the acquisition and retention trade-off.

Startup companies boost the quality of everyday life in almost all dimensions, and their products and services are of relevance everywhere. One of the most important goals that startups pursue is to increase the number of their users ...

• Redefining request under the term “rweet” in the context of social networking sties, as well as defining its primary types and subtypes.

Catastrophic events create uncertain situations for humanitarian organizations locating and providing aid to affected people. Many people turn to social media during disasters for requesting help and/or providing relief to others. ...

• Symbiotic organism search algorithm with random walk and mutation is proposed.
• ...

Sleep staging can objectively evaluate sleep quality to effectively assist in preventing and diagnosing sleep disorder. Because of the multi-channel and multi-model characteristics of physiological signals, high-dimensional features ...

• Propose an item attraction model for session-based recommendation.
• Convert ...

Session-based recommendation uses existing items in users’ interaction sessions to predict the next items with which users will interact. The existing items in sessions usually have different degrees of relevance with each other, and ...

• Proposed computation framework for Big hyperspectral data discriminate analytics.

Recent technology developments in hyperspectral sensing has made it possible to acquire several hundred spectral bands that cover the electromagnetic spectrum of an observational scene in a single acquisition. The resulting ...

• Investigating merits of dual point operators towards Pythagorean membership grades.

Considering the new uncertainty format of Pythagorean fuzzy (PF) sets, this research aims to launch a point operator-based likelihood measure and establish a PF preference ranking organization method for enrichment evaluations (...