The data are provided to illustrate methods in evaluating systematic transactional data reuse in machine learning. A library account-based recommender system was developed using machine learning processing over transactional data of 383,828 transactions (or check-outs) sourced from a large multi-unit research library. The machine learning process utilized the FP-growth algorithm over the subject metadata associated with physical items that were checked-out together in the library. The purpose of this research is to evaluate the results of systematic transactional data reuse in machine learning. The analysis herein contains a large-scale network visualization of 180,441 subject association rules and corresponding node metrics.

Source Paper

This dataset is from my paper:

Heaton, J. (2016, March). Comparing dataset characteristics that favor the Apriori, Eclat or FP-Growth frequent itemset mining algorithms. In SoutheastCon 2016 (pp. 1-7). IEEE.

Frequent itemset mining is a popular data mining technique. Apriori, Eclat, and FP-Growth are among the most common algorithms for frequent itemset mining. Considerable research has been performed to compare the relative performance between these three algorithms, by evaluating the scalability of each algorithm as the dataset size increases. While scalability as data size increases is important, previous papers have not examined the performance impact of similarly sized datasets that contain different itemset characteristics. This paper explores the effects that two dataset characteristics can have on the performance of these three frequent itemset algorithms. To perform this empirical analysis, a dataset generator is created to measure the effects of frequent item density and the maximum transaction size on performance. The generated datasets contain the same number of rows. This provides some insight into dataset characteristics that are conducive to each algorithm. The results of this paper's research demonstrate Eclat and FP-Growth both handle increases in maximum transaction size and frequent itemset density considerably better than the Apriori algorithm.

Files Generated

We generated two datasets that allow us to adjust two independent variables to create a total of 20 different transaction sets. We also provide the Python script that generated this data in a notebook. This Python script accepts the following parameters to specify the transaction set to produce:

• Transaction/Basket count: 5 million default
• Number of items: 50,000 default
• Number of frequent sets: 100 default
• Max transaction/basket size: independent variable, 5-100 range
• Frequent set density: independent variable, 0.1 to 0.8 range

Files contained in this dataset reside in two folders: * freq-items-pct - We vary the frequent set density in these transaction sets. * freq-items-tsz - We change the maximum number of items per basket in these transaction sets.

While you can vary basket count, the number of frequent sets, and the number of items in the script, they will remain fixed at this paper's above values. We determined that the basket count only had a small positive correlation.

File Content

The following listing shows the type of data generated for this research. Here we present an example file created with ten baskets out of 100 items, two frequent itemsets, a maximum basket size of 10, and a density of 0.5.

I36 I94 
I71 I13 I91 I89 I34
F6 F5 F3 F4 
I86 
I39 I16 I49 I62 I31 I54 I91 
I22 I31 
I70 I85 I78 I63 
F4 F3 F1 F6 F0 I69 I44 
I82 I50 I9 I31 I57 I20 
F4 F3 F1 F6 F0 I87

As you can see from the above file, the items are either prefixed with “I” or “F.” The “F” prefix indicates that this line contains one of the frequent itemsets. Items with the “I” prefix are not part of an intentional frequent itemset. Of course, “I” prefixed items might form frequent itemsets, as they are uniformly sampled from the number of things to fill out nonfrequent itemsets. Each basket will have a random size chosen, up to the maximum basket size. The frequent itsemset density specifies the probability of each line containing one of the intentional frequent itemsets. Because we used a density of 0.5, approximately half of the lines above include one of the two intentional frequent itemsets. A frequent itemset line may have additional random “I” prefixed items added to cause the line to reach the randomly chosen length for that line. If the frequent itemset selected does cause the generated sequence to exceed its randomly chosen length, no truncation will occur. The intentional frequent itemsets are all determined to be less than or equal to the maximum basket size.

Dataset

This dataset was created by Sena Negara

Contents

Yearly citation counts for the publication titled "A new FP-tree-based algorithm MMFI for mining the maximal frequent itemsets".

An enhanced method to mine rare item sets using multiple item sets support based on cp tree Rare Association rule is an association rule consisting of rare items Frequent Pattern FP growth is an approach for utilizes the preceding knowledge providing by the user at the time of input and discovers frequent patterns with a two scan on the transactional dataset We are presented a CP tree Compact pattern tree that capture database information with one scan Insertion phase and provided th

Generated datasets for frequent itemset mining algorithms Apriori, Eclat, and FP-Growth.

The FP-tree in Example 1.

Mined rules by FP-Growth algorithm.

Essa conjunto de dados está organizado da seguinte forma:

• bateria de testes de 1 a 7 com os algoritmos Apriori e FPGrowth (Ex.: Apriori - 1 bateria e FPGrowth - 1 bateria);
• regras extraídas para as questões de pesquisa por algoritmo (Ex.: AprioriQ1 e FPGrowthQ1);
• Bases de dados utilizadas (Ex.: BaseSIVEPConf).

This dataset presents a collection of co-existence features extracted from the original CICMalDroid 2020 using the FP-Growth algorithm. The co-existence features are combinations of two features that frequently occur together within the dataset.

Network of 30 papers and 43 citation links related to "A new FP-tree-based algorithm MMFI for mining the maximal frequent itemsets".

Additional file 1. Table 1. Disease generalization in ICD-10 codes. Table 2. Comparison among OMOP ID, Concept Code and the generlization ICD-10 codes. Table 3. The rules verified by literatures. Table 4. The rules discoveried by FP-growth algorithm.

The Fabry-Perot (FP) Laser Diode (LD) market is experiencing robust growth, driven by increasing demand across diverse sectors. The market's expansion is fueled by advancements in miniaturization and improved performance characteristics of FP LDs, making them increasingly suitable for applications requiring high speed, precision, and compactness. The industrial sector, particularly automation and manufacturing processes, is a significant contributor to market growth, with FP LDs finding applications in sensing, measurement, and material processing. The electronics and communication sectors also represent substantial market segments, leveraging FP LDs in optical communication systems, data centers, and high-speed networking. Optical research utilizes FP LDs for advanced scientific instrumentation and experimental setups, while the medical sector benefits from their precision in laser surgery and diagnostic imaging. The market is segmented by application (industrial, electronics, communication, optical research, others) and type (butterfly package, dual inline package). While the butterfly package currently dominates due to its compact size and ease of integration, the dual inline package is gaining traction owing to its cost-effectiveness and suitability for high-power applications. Competition among manufacturers such as Fibercom, Inphenix, and Thorlabs is intense, with a focus on innovation, product differentiation, and cost optimization. The global market is geographically diverse, with North America and Asia Pacific exhibiting the strongest growth, driven by technological advancements and robust industrial growth in these regions. Future market growth will be influenced by technological innovations, including the development of higher-power, more energy-efficient, and cost-effective FP LDs, coupled with expanding applications in emerging technologies like 5G and autonomous driving. The market's CAGR, although not explicitly provided, can be reasonably estimated based on typical growth rates observed in the optoelectronics industry. Assuming a conservative yet realistic CAGR of 8% based on current market trends and technological advancements, the market size is projected to experience substantial growth over the forecast period (2025-2033). This growth trajectory is expected to continue to be influenced by the factors mentioned above, alongside potential regulatory changes and evolving consumer preferences. Continued innovation in packaging technologies, material science, and manufacturing processes will be crucial to maintain the market’s competitiveness and accommodate the expanding applications of FP LDs. This ongoing development ensures the FP LD market remains a dynamic and lucrative space for stakeholders, attracting continued investment and fostering further expansion.

Colombia Total Factor Productivity (FP): Value-Added Growth (VG) data was reported at 1.359 % in 2024. This records an increase from the previous number of -1.072 % for 2023. Colombia Total Factor Productivity (FP): Value-Added Growth (VG) data is updated yearly, averaging -0.094 % from Dec 2005 (Median) to 2024, with 20 observations. The data reached an all-time high of 4.231 % in 2006 and a record low of -2.682 % in 2007. Colombia Total Factor Productivity (FP): Value-Added Growth (VG) data remains active status in CEIC and is reported by National Administrative Department of Statistics. The data is categorized under Global Database’s Colombia – Table CO.G075: Total Factor Productivity.

Fabry Perot (FP) Laser Diode (LD) Market Outlook

The global Fabry Perot (FP) Laser Diode (LD) market size was valued at approximately USD 1.2 billion in 2023 and is projected to reach around USD 2.8 billion by 2032, growing at a Compound Annual Growth Rate (CAGR) of 9.5% during the forecast period. This significant growth can be attributed to rising demand for high-speed data transmission, advancements in telecommunication infrastructure, and increasing utilization in various industrial applications. The proliferation of the Internet of Things (IoT), 5G technology, and growing data center investments are key drivers fueling the market's expansion.

The growth of the FP Laser Diode market is primarily driven by the expanding telecommunications sector. With the adoption of 5G technology, there is a surging demand for high-speed and efficient data transmission, which FP laser diodes facilitate due to their superior performance characteristics. Additionally, the rapid expansion of data centers to accommodate the growing data traffic further boosts the demand for these laser diodes. The ongoing shift towards cloud computing and IoT devices necessitates robust and reliable communication infrastructure, driving the market's growth.

Another significant growth factor is the increasing application of FP laser diodes in the medical sector. These diodes are extensively used in medical devices for procedures like optical coherence tomography (OCT), laser surgeries, and diagnostic imaging. The rising prevalence of chronic diseases and the need for advanced diagnostic tools create substantial demand in this segment. Moreover, the continuous advancements in medical technology further enhance the adoption of FP laser diodes, contributing to market growth.

Industrial applications also play a crucial role in the market expansion. FP laser diodes are utilized in various industrial processes including material processing, cutting, welding, and surface treatment due to their precision and efficiency. The growing automation and adoption of smart manufacturing practices are fostering the use of advanced laser technologies, propelling the market growth. Additionally, the defense sector's increasing investment in laser-based systems for communication and targeting further supports the market development.

Regionally, the Asia Pacific market is poised for significant growth, driven by rapid industrialization, technological advancements, and substantial investments in telecommunications infrastructure. Countries like China, Japan, and South Korea are at the forefront of technological innovation, contributing to the high demand for FP laser diodes in various applications. Moreover, the region's expanding consumer electronics industry and the increasing number of data centers are expected to further enhance market growth over the forecast period.

The introduction of the 25G DFB Laser Chip has marked a significant advancement in the field of optical communication. These chips are designed to offer high-speed data transmission capabilities, making them essential for modern telecommunication networks. With the increasing demand for faster internet speeds and more reliable connections, the 25G DFB Laser Chip plays a crucial role in enhancing the efficiency of data centers and telecommunication infrastructures. Its ability to provide stable and coherent laser outputs makes it an ideal choice for long-distance fiber optic communications, supporting the growing needs of 5G networks and IoT applications. As industries continue to evolve, the integration of 25G DFB Laser Chips is expected to drive further innovations in data transmission technologies.

Type Analysis

The market for Fabry Perot Laser Diodes is segmented by type into Single-Mode and Multi-Mode. Single-Mode FP laser diodes are favored for applications requiring high precision and coherence, such as scientific research and high-resolution imaging. The demand for Single-Mode FP laser diodes is increasing due to their ability to provide stable and narrow linewidth outputs, essential for advanced applications in telecommunications and medical diagnostics. The ongoing research and development activities aimed at improving the efficiency and performance of Single-Mode diodes are likely to further augment their market share.

Multi-Mode FP laser diodes, on the other hand, find extensive usage in applications where high power and broad spectral outputs are required. T

The global Fabry-Perot(FP) Laser Diode (LD) market is projected to grow from USD XXX million in 2023 to USD XXX million by 2030, at a CAGR of XX% during the forecast period. The market is driven by the increasing demand for high-power lasers in various applications such as telecommunications, industrial processing, and medical devices. FP LDs offer advantages such as high power output, narrow linewidth, and low noise, making them ideal for these applications. The market is also witnessing the development of new technologies, such as VCSELs (Vertical-Cavity Surface-Emitting Lasers), which are expected to further boost the market growth. The key players in the market include Fibercom, Inphenix, Nanoplus, Sheaumann, Thorlabs, Timbercon, LD-PD, Changchun New Industries Optoelectronics, Toptica Photonics, MKS, Laser light Solutions, CNI Laser, CEL, MACOM, Brolis Semiconductors, Mir Sense, OSI Laser Diode, Optilab, Anritsu, CNI Laser, and Hanwei Electronics Group Corporation. The market is fragmented, with numerous small and medium-sized players. The key players are focusing on developing new technologies and expanding their product offerings to gain market share.

The article is scheduled to be published in 2025 in the online scientific journal Actual Problems of Oil and Gas (https://oilgasjournal.ru).Abstract. Background. Hydrogen is given the role of a clean energy carrier in the energy transition. Objective. To identify relevant research topics based on pooled bibliometric data of the International Journal of Hydrogen Energy publications from 2022–2024, collected from The Lens and ScienceDirect platforms. Materials and methods. 10,928 bibliometric records were exported from The Lens database and 10,857 records were exported from ScienceDirect. Keywords clustering and visual data analysis were performed using the following programs and algorithms: VOSviewer, Scimago Graphica, Inkscape, FP-growth utility. Results. The study showed the feasibility of merging bibliometric records from the open platforms ScienceDirect and The Lens, which complement each other. The “Fields of Study” data of The Lens was interpreted as system keywords similar to Scopus Index Keywords. The possibility of using “Fields of Study” data in a method similar to bibliographic coupling is shown. The practicality of using an alluvial diagram to show the co-occurrence of the four terms was demonstrated. The study also emphasizes the advisability of joint use of VOSviewer and Scimago Graphica programs for complex visualization of bibliometric analysis results. The study identified two dominant publication topics in the International Journal of Hydrogen Energy for 2022–2024, which can be described in terms of: “Catalysis, Hydrogen, Physical_chemistry, Chemical_engineering, Nanotechnology, Electrochemistry, Organic_chemistry, Materials_science” and “Electrical_engineering, Hydrogen_production, Renewable_energy, Environmental_science, Hydrogen_economy, Hydrogen, Engineering”. Conclusions. Joint use of metadata of different open abstract databases allows to compensate partial representation of their data.

Metastatic breast cancer triplet mutations in FP Growth tree.

Additional file 2. FP-GRowth : Most frequents itemsets.

Introduction: Motilin (MLN) is a gastrointestinal (GI) hormone produced in the upper small intestine. Its most well understood function is to participate in Phase III of the migrating myoelectric complex component of GI motility. Changes in MLN availability are associated with GI diseases such as gastroesophageal reflux disease and functional dyspepsia. Furthermore, herbal medicines have been used for several years to treat various GI disorders. We systematically reviewed clinical and animal studies on how herbal medicine affects the modulation of MLN and subsequently brings the therapeutic effects mainly focused on GI function.Methods: We searched the PubMed, Embase, Cochrane, and Web of Science databases to collect all articles published until 30 July 2023, that reported the measurement of plasma MLN levels in human randomized controlled trials and in vivo herbal medicine studies. The collected characteristics of the articles included the name and ingredients of the herbal medicine, physiological and symptomatic changes after administering the herbal medicine, changes in plasma MLN levels, key findings, and mechanisms of action. The frequency patterns (FPs) of botanical drug use and their correlations were investigated using an FP growth algorithm.Results: Nine clinical studies with 1,308 participants and 20 animal studies were included in the final analyses. Herbal medicines in clinical studies have shown therapeutic effects in association with increased levels of MLN, including GI motility regulation and symptom improvement. Herbal medicines have also shown anti-stress, anti-tumor, and anti-inflammatory effects in vivo. Various biochemical markers may correlate with MLN levels. Markers may have a positive correlation with plasma MLN levels included ghrelin, acetylcholine, and secretin, whereas a negative correlation included triglycerides and prostaglandin E2. Markers, such as gastrin and somatostatin, did not show any correlation with plasma MLN levels. Based on the FP growth algorithm, Glycyrrhiza uralensis and Paeonia japonica were the most frequently used species.Conclusion: Herbal medicine may have therapeutic effects mainly on GI symptoms with involvement of MLN regulation and may be considered as an alternative option for the treatment of GI diseases. Further studies with more solid evidence are needed to confirm the efficacy and mechanisms of action of herbal medicines.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=443244, identifier CRD42023443244.