Extraction System Web Content Sports New Based On Web Crawler Multi Thread

Pramudita, Yoga Dwitya; Anamisa, Devie Rosa; Putro, Sigit Susanto; Rahmawanto, M A

doi:10.1088/1742-6596/1569/2/022077

Cited by 4 publications

(3 citation statements)

References 5 publications

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“…In and Pramudita et al (2020) authors designed a heterogeneous collaborative edge cache framework by jointly optimizing node selection and cache replacement in mobile networks. The joint optimization problem is expressed as a Markov Decision Process (MDP), and Deep Q Network (DQN) is used to solve the problem, which alleviates the offloading traffic load.…”

Section: Related Workmentioning

confidence: 99%

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Analysis of Multi-Threading and Cache Memory Latency Masking on Processor Performance Using Thread Synchronization Technique

Ehis

2023

Braz. J. of Sci.

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Multithreading is a process in which a single processor executes multiple threads concurrently. This enables the processor to divide tasks into separate threads and run them simultaneously, thereby increasing the utilization of available system resources and enhancing performance. When multiple threads share an object and one or more of them modify it, unpredictable outcomes may occur. Threads that exhibit poor locality of memory reference, such as database applications, often experience delays while waiting for a response from the memory hierarchy. This observation suggests how to better manage pipeline contention. To assess the impact of memory latency on processor performance, a dual-core MT machine with four thread contexts per core is utilized. These specific benchmarks are chosen to allow the workload to include programs with both favorable and unfavorable cache locality. To eliminate the issue of wasting the wake-up signals, this work proposes an approach that involves storing all the wake-up calls. It asserts the wake-up calls to the consumer and the producer can store the wake-up call in a variable. An assigned value in working system (or kernel) storage that each process can check is a semaphore. Semaphore is a variable that reads, and update operations automatically in bit mode. It cannot be actualized in client mode since a race condition may persistently develop when two or more processors endeavor to induce to the variable at the same time. This study includes code to measure the time taken to execute both functions and plot the graph. It should be noted that sending multiple requests to a website simultaneously could trigger a flag, ultimately blocking access to the data. This necessitates some computation on the collected statistics. The execution time is reduced to one third when using threads compared to executing the functions sequentially. This exemplifies the power of multithreading.

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Section: Related Workmentioning

confidence: 99%

“…Murthy & Rani (2022) and Fu et al (2022) describe a model for multi-processor IPC based on cache miss rates (Pramudita et al, 2020. Their model of cache delays for single-threaded workloads uses a similar approach.…”

Section: Related Workmentioning

confidence: 99%

Analysis of Multi-Threading and Cache Memory Latency Masking on Processor Performance Using Thread Synchronization Technique

Ehis

2023

Braz. J. of Sci.

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“…Other studies used particular techniques for efficient scraping such as the work of Pramudita et al [9] who used a multithreaded technique to construct the web crawler program. In [10], the authors covered the topics of web crew members, including their designs, and other difficulties that arise when search engines utilize Web crawlers.…”

Section: Introductionmentioning

confidence: 99%

A Web Scraper for Data Mining Purposes

Mahmood,

Mahmood

2024

SISTEMASI

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The current revolution in technology makes data a crucial part of real-life applications due to its importance in making decisions. In the era of big data and the massive expansion of data streams on Internet networks and platforms, the process of data collection, mining, and analysis has become a not easy matter. Therefore, the presence of auxiliary applications for data mining and gathering has become a necessary need. Usually, companies offer special APIs to collect data from particular destinations, which needs a high cost. Generally, there is a severe lack in the literature in providing approaches that offer flexible, low, or free of cost tools for web scraping. Hence, this article provides a free tool that can be used for data mining and data collection purposes from the web. Specifically, an efficient Google Scholar web scraper is introduced. The extracted data can be used for analysis purposes and making decisions about an issue of interest. The proposed scraper can also be modified for crawling web links and retrieving specific data from a particular website. It can also formalize the collected data as a ready dataset to be used in the analysis phase. The efficiency of the proposed scraper is tested in terms of the time consumption, accuracy, and quality of the data collected. The findings showed that the proposed approach is highly feasible for data collection and can be adopted by data analysts.

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