Upgraded SemIndex Prototype Supporting Intelligent Database Keyword Queries through Disambiguation, Query as You Type, and Parallel Search Algorithms by Tekli, Joe

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RHEEMix in the data jungle: a cost-based optimizer for cross-platform systems. by Sebastian Kruse (18595195)

PERF solutions for distributed query optimization. (c1999) by Fany, Roula

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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data by Rajesh Kumar Dhanaraj (19646269)

“…Experiments are conducted to evaluate the performance of the RFBXSQLQC technique using the IIT Bombay dataset using the metrics like antipattern detection accuracy, time complexity, false-positive rate, and computational overhead with respect to the differing number of queries. The results revealed that the RFBXSQLQC technique outperforms the existing algorithms by 19% with pattern detection accuracy, 34% minimized time complexity, 64% false-positive rate, and 31% in terms of computational overhead.…”

Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying by Tekli, Joe

“…Many efforts have been deployed by the IR community to extend freetext query processing toward semi-structured XML search. …”
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Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS by Tekli, Joe

“…We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm by Nasr, Joshua

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Assessment of network module identification across complex diseases by Sarvenaz Choobdar (18602821)

“…Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies. Our robust assessment of 75 module identification methods reveals top-performing algorithms, which recover complementary trait-associated modules. …”

How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation by Joni Salminen (7434770)

“…The results from extracting information from 172 relevant articles show that algorithmic customer segmentation is the predominant approach for customer segmentation. …”

Optimizing Document Classification: Unleashing the Power of Genetic Algorithms by Ghulam Mustafa (458105)

“…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …”

A hybrid graph representation for recursive backtracking algorithms by Abu-Khzam, Faisal N.

“…The performance of these algorithms often suffers from the increasing number of graph modifications, such as deletions, that reduce the problem instance and have to be “taken back” frequently during the search process. …”
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Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

“…Moreover, we also presented the challenges of metaheuristic algorithms for feature selection, and we identified gaps for further research studies.…”
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Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study by Alaa Abd-alrazaq (17058018)

“…Our BERTopic-based approach involves 3 stages: embedding documents, clustering documents (dimension reduction and clustering), and representing topics (generating candidates and maximizing candidate relevance).</p><h3>Results</h3><p dir="ltr">After applying the study selection criteria, we included 33,206 abstracts in the analysis of this study. …”

Performance assessment and exhaustive listing of 500+ nature-inspired metaheuristic algorithms by Zhongqiang Ma (13765801)

“…Generally, the inventors attribute the novelties of these new algorithms to inspirations from either biology, human behaviors, physics, or other phenomena. …”

Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System by Abualigah, Laith

“…Efficient speed controllers for dynamic driving tasks in autonomous vehicles are crucial for ensuring safety and reliability. This study proposes a novel approach for designing a fractional order proportional-integral-derivative (FOPID) controller that utilizes a modified elite opposition-based artificial hummingbird algorithm (m-AHA) for optimal parameter tuning. …”
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

“…To overcome these challenges, a new FS algorithm named Uniform-solution-driven Binary Feature Selection (UniBFS) has been developed in this study. …”

Properties of Unique Degree Sequences of 3-Uniform Hypergraphs by Tarsissi, Lama

“…In particular, our study concerns 3-uniform hypergraphs that are defined in the NP-completeness proof of Deza et al. …”
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An efficient failure-resilient mutual exclusion algorithm for distributed systems leveraging a novel zero-message overlay structure by Mouna Rabhi (17086969)

“…An extensive simulation study demonstrates the viability and efficiency of the proposed algorithm under various node failure models, and relevant metrics (e.g., node queue dimension, number of exchanged messages, and number of disconnected nodes) indicate a graceful degradation in performance with decreasing number of functioning nodes. …”

Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis by Hassan, Ali

“…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities by Mahdi Mokhtarzadeh (11593310)

“…The results indicate that KNSGA-II is superior to other algorithms. Also, a case study in Iran is implemented and the related results are analyzed.…”