Data Mining and Knowledge Discovery最新文献_第8页

Correction: A semi‑supervised interactive algorithm for change point detection 更正：用于变化点检测的半监督交互式算法

IF 4.8 3区计算机科学

Data Mining and Knowledge Discovery Pub Date : 2024-01-02 DOI: 10.1007/s10618-023-01000-z

Zhenxiang Cao, N. Seeuws, Maarten Vos, Alexander Bertrand

引用次数: 0

Predicting consumer choice from raw eye-movement data using the RETINA deep learning architecture 利用 RETINA 深度学习架构从原始眼动数据中预测消费者选择

IF 4.8 3区计算机科学

Data Mining and Knowledge Discovery Pub Date : 2023-12-29 DOI: 10.1007/s10618-023-00989-7

Moshe Unger, Michel Wedel, Alexander Tuzhilin

{"title":"Predicting consumer choice from raw eye-movement data using the RETINA deep learning architecture","authors":"Moshe Unger, Michel Wedel, Alexander Tuzhilin","doi":"10.1007/s10618-023-00989-7","DOIUrl":"https://doi.org/10.1007/s10618-023-00989-7","url":null,"abstract":"We propose the use of a deep learning architecture, called RETINA, to predict multi-alternative, multi-attribute consumer choice from eye movement data. RETINA directly uses the complete time series of raw eye-tracking data from both eyes as input to state-of-the art Transformer and Metric Learning Deep Learning methods. Using the raw data input eliminates the information loss that may result from first calculating fixations, deriving metrics from the fixations data and analysing those metrics, as has been often done in eye movement research, and allows us to apply Deep Learning to eye tracking data sets of the size commonly encountered in academic and applied research. Using a data set with 112 respondents who made choices among four laptops, we show that the proposed architecture outperforms other state-of-the-art machine learning methods (standard BERT, LSTM, AutoML, logistic regression) calibrated on raw data or fixation data. The analysis of partial time and partial data segments reveals the ability of RETINA to predict choice outcomes well before participants reach a decision. Specifically, we find that using a mere 5 s of data, the RETINA architecture achieves a predictive validation accuracy of over 0.7. We provide an assessment of which features of the eye movement data contribute to RETINA’s prediction accuracy. We make recommendations on how the proposed deep learning architecture can be used as a basis for future academic research, in particular its application to eye movements collected from front-facing video cameras.","PeriodicalId":55183,"journal":{"name":"Data Mining and Knowledge Discovery","volume":"29 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139064560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Session-based recommendation by exploiting substitutable and complementary relationships from multi-behavior data 利用多行为数据中的可替代和互补关系，进行基于会话的推荐

IF 4.8 3区计算机科学

Data Mining and Knowledge Discovery Pub Date : 2023-12-26 DOI: 10.1007/s10618-023-00994-w

Huizi Wu, Cong Geng, Hui Fang

{"title":"Session-based recommendation by exploiting substitutable and complementary relationships from multi-behavior data","authors":"Huizi Wu, Cong Geng, Hui Fang","doi":"10.1007/s10618-023-00994-w","DOIUrl":"https://doi.org/10.1007/s10618-023-00994-w","url":null,"abstract":"Session-based recommendation (SR) aims to dynamically recommend items to a user based on a sequence of the most recent user-item interactions. Most existing studies on SR adopt advanced deep learning methods. However, the majority only consider a special behavior type (e.g., click), while those few considering multi-typed behaviors ignore to take full advantage of the relationships between products (items). In this case, the paper proposes a novel approach, called Substitutable and Complementary Relationships from Multi-behavior Data (denoted as SCRM) to better explore the relationships between products for effective recommendation. Specifically, we firstly construct substitutable and complementary graphs based on a user’s sequential behaviors in every session by jointly considering ‘click’ and ‘purchase’ behaviors. We then design a denoising network to remove false relationships, and further consider constraints on the two relationships via a particularly designed loss function. Extensive experiments on two e-commerce datasets demonstrate the superiority of our model over state-of-the-art methods, and the effectiveness of every component in SCRM.","PeriodicalId":55183,"journal":{"name":"Data Mining and Knowledge Discovery","volume":"37 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139057144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Random walk with restart on hypergraphs: fast computation and an application to anomaly detection 超图上重新开始的随机行走：快速计算及异常检测应用

IF 4.8 3区计算机科学

Data Mining and Knowledge Discovery Pub Date : 2023-12-21 DOI: 10.1007/s10618-023-00995-9

Jaewan Chun, Geon Lee, Kijung Shin, Jinhong Jung

{"title":"Random walk with restart on hypergraphs: fast computation and an application to anomaly detection","authors":"Jaewan Chun, Geon Lee, Kijung Shin, Jinhong Jung","doi":"10.1007/s10618-023-00995-9","DOIUrl":"https://doi.org/10.1007/s10618-023-00995-9","url":null,"abstract":"Random walk with restart (RWR) is a widely-used measure of node similarity in graphs, and it has proved useful for ranking, community detection, link prediction, anomaly detection, etc. Since RWR is typically required to be computed separately for a larger number of query nodes or even for all nodes, fast computation of it is indispensable. However, for hypergraphs, the fast computation of RWR has been unexplored, despite its great potential. In this paper, we propose ARCHER, a fast computation framework for RWR on hypergraphs. Specifically, we first formally define RWR on hypergraphs, and then we propose two computation methods that compose ARCHER. Since the two methods are complementary (i.e., offering relative advantages on different hypergraphs), we also develop a method for automatic selection between them, which takes a very short time compared to the total running time. Through our extensive experiments on 18 real-world hypergraphs, we demonstrate (a) the speed and space efficiency of ARCHER, (b) the complementary nature of the two computation methods composing ARCHER, (c) the accuracy of its automatic selection method, and (d) its successful application to anomaly detection on hypergraphs.","PeriodicalId":55183,"journal":{"name":"Data Mining and Knowledge Discovery","volume":"69 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138823850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving hyper-parameter self-tuning for data streams by adapting an evolutionary approach 通过调整进化方法改进数据流的超参数自调整

IF 4.8 3区计算机科学

Data Mining and Knowledge Discovery Pub Date : 2023-12-21 DOI: 10.1007/s10618-023-00997-7

Antonio R. Moya, Bruno Veloso, João Gama, Sebastián Ventura

引用次数: 0

OEC: an online ensemble classifier for mining data streams with noisy labels OEC：用于挖掘带噪声标签数据流的在线集合分类器

IF 4.8 3区计算机科学

Data Mining and Knowledge Discovery Pub Date : 2023-12-12 DOI: 10.1007/s10618-023-00990-0

Ling Jian, Kai Shao, Ying Liu, Jundong Li, Xijun Liang

{"title":"OEC: an online ensemble classifier for mining data streams with noisy labels","authors":"Ling Jian, Kai Shao, Ying Liu, Jundong Li, Xijun Liang","doi":"10.1007/s10618-023-00990-0","DOIUrl":"https://doi.org/10.1007/s10618-023-00990-0","url":null,"abstract":"Distilling actionable patterns from large-scale streaming data in the presence of concept drift is a challenging problem, especially when data is polluted with noisy labels. To date, various data stream mining algorithms have been proposed and extensively used in many real-world applications. Considering the functional complementation of classical online learning algorithms and with the goal of combining their advantages, we propose an Online Ensemble Classification (OEC) algorithm to integrate the predictions obtained by different base online classification algorithms. The proposed OEC method works by learning weights of different base classifiers dynamically through the classical Normalized Exponentiated Gradient (NEG) algorithm framework. As a result, the proposed OEC inherits the adaptability and flexibility of concept drift-tracking online classifiers, while maintaining the robustness of noise-resistant online classifiers. Theoretically, we show OEC algorithm is a low regret algorithm which makes it a good candidate to learn from noisy streaming data. Extensive experiments on both synthetic and real-world datasets demonstrate the effectiveness of the proposed OEC method.","PeriodicalId":55183,"journal":{"name":"Data Mining and Knowledge Discovery","volume":"177 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138628812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Structure-aware decoupled imputation network for multivariate time series 多变量时间序列的结构感知解耦归因网络

IF 4.8 3区计算机科学

Data Mining and Knowledge Discovery Pub Date : 2023-12-08 DOI: 10.1007/s10618-023-00987-9

Nourhan Ahmed, Lars Schmidt-Thieme

{"title":"Structure-aware decoupled imputation network for multivariate time series","authors":"Nourhan Ahmed, Lars Schmidt-Thieme","doi":"10.1007/s10618-023-00987-9","DOIUrl":"https://doi.org/10.1007/s10618-023-00987-9","url":null,"abstract":"Handling incomplete multivariate time series is an important and fundamental concern for a variety of domains. Existing time-series imputation approaches rely on basic assumptions regarding relationship information between sensors, posing significant challenges since inter-sensor interactions in the real world are often complex and unknown beforehand. Specifically, there is a lack of in-depth investigation into (1) the coexistence of relationships between sensors and (2) the incorporation of reciprocal impact between sensor properties and inter-sensor relationships for the time-series imputation problem. To fill this gap, we present the Structure-aware Decoupled imputation network (SaD), which is designed to model sensor characteristics and relationships between sensors in distinct latent spaces. Our approach is equipped with a two-step knowledge integration scheme that incorporates the influence between the sensor attribute information as well as sensor relationship information. The experimental results indicate that when compared to state-of-the-art models for time-series imputation tasks, our proposed method can reduce error by around 15%.","PeriodicalId":55183,"journal":{"name":"Data Mining and Knowledge Discovery","volume":"107 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138555888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Outcomes and Surgical Nuances of Minimally Invasive Parotid Surgery for Pleomorphic Adenoma. 微创腮腺手术治疗多形性腺瘤的疗效及手术特点。

IF 2.8 3区计算机科学

Data Mining and Knowledge Discovery Pub Date : 2023-12-01 Epub Date: 2023-06-19 DOI: 10.1007/s12070-023-03947-3

Kalyana Sundaram Chidambaram, Manjul Muraleedharan, Amit Keshri, Sabaratnam Mayilvaganan, Nazrin Hameed, Mohd Aqib, Arushi Kumar, Ravi Sankar Manogaran, Raj Kumar

{"title":"The Outcomes and Surgical Nuances of Minimally Invasive Parotid Surgery for Pleomorphic Adenoma.","authors":"Kalyana Sundaram Chidambaram, Manjul Muraleedharan, Amit Keshri, Sabaratnam Mayilvaganan, Nazrin Hameed, Mohd Aqib, Arushi Kumar, Ravi Sankar Manogaran, Raj Kumar","doi":"10.1007/s12070-023-03947-3","DOIUrl":"10.1007/s12070-023-03947-3","url":null,"abstract":"Benign parotid tumors follow an indolent course and present as slow-growing painless swelling in the pre-and-infra-auricular areas. The treatment of choice is surgery. Though the gold standard technique is Superficial Parotidectomy, Extracapsular Dissection (ECD) is an alternative option with the same outcome and decreased complications. This study discusses our experience with extracapsular dissection and the surgical nuances for better results. A retrospective study of histologically confirmed cases of pleomorphic adenoma of the parotid gland, who underwent Extracapsular dissection between September 2019 and March 2023, was done. The demographic details, clinical characteristics, and outcomes were evaluated. There were 33 patients, including 16 females and 17 males, with a mean age of 32.75 years. All cases presented as slow-growing painless swelling for a mean duration of 5 years. Most of the tumors (94%) were of size between 2 and 4 cm, with few tumors more than 4 cm. All underwent extracapsular dissection with complete excision. There was only one complication (seroma) and no incidence of facial palsy in our experience with ECD. The goal of a benign parotid surgery is the complete removal of the tumor with minimum complications, which could be achieved with ECD, which has good tumor clearance and lesser rates of complications with good cosmesis. Thus, this minimally invasive parotid surgery could be a worthwhile option in properly selected cases.","PeriodicalId":55183,"journal":{"name":"Data Mining and Knowledge Discovery","volume":"28 1","pages":"3256-3262"},"PeriodicalIF":2.8,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10645680/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73804083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Navigating the metric maze: a taxonomy of evaluation metrics for anomaly detection in time series 导航度量迷宫:在时间序列中异常检测的评估度量的分类

IF 4.8 3区计算机科学

Data Mining and Knowledge Discovery Pub Date : 2023-11-18 DOI: 10.1007/s10618-023-00988-8

Sondre Sørbø, Massimiliano Ruocco

{"title":"Navigating the metric maze: a taxonomy of evaluation metrics for anomaly detection in time series","authors":"Sondre Sørbø, Massimiliano Ruocco","doi":"10.1007/s10618-023-00988-8","DOIUrl":"https://doi.org/10.1007/s10618-023-00988-8","url":null,"abstract":"The field of time series anomaly detection is constantly advancing, with several methods available, making it a challenge to determine the most appropriate method for a specific domain. The evaluation of these methods is facilitated by the use of metrics, which vary widely in their properties. Despite the existence of new evaluation metrics, there is limited agreement on which metrics are best suited for specific scenarios and domains, and the most commonly used metrics have faced criticism in the literature. This paper provides a comprehensive overview of the metrics used for the evaluation of time series anomaly detection methods, and also defines a taxonomy of these based on how they are calculated. By defining a set of properties for evaluation metrics and a set of specific case studies and experiments, twenty metrics are analyzed and discussed in detail, highlighting the unique suitability of each for specific tasks. Through extensive experimentation and analysis, this paper argues that the choice of evaluation metric must be made with care, taking into account the specific requirements of the task at hand.","PeriodicalId":55183,"journal":{"name":"Data Mining and Knowledge Discovery","volume":"13 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2023-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138540835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Anomaly detection in sleep: detecting mouth breathing in children 睡眠异常检测:儿童口部呼吸检测

3区计算机科学

Data Mining and Knowledge Discovery Pub Date : 2023-11-13 DOI: 10.1007/s10618-023-00985-x

Luka Biedebach, María Óskarsdóttir, Erna Sif Arnardóttir, Sigridur Sigurdardóttir, Michael Valur Clausen, Sigurveig Þ. Sigurdardóttir, Marta Serwatko, Anna Sigridur Islind

{"title":"Anomaly detection in sleep: detecting mouth breathing in children","authors":"Luka Biedebach, María Óskarsdóttir, Erna Sif Arnardóttir, Sigridur Sigurdardóttir, Michael Valur Clausen, Sigurveig Þ. Sigurdardóttir, Marta Serwatko, Anna Sigridur Islind","doi":"10.1007/s10618-023-00985-x","DOIUrl":"https://doi.org/10.1007/s10618-023-00985-x","url":null,"abstract":"Abstract Identifying mouth breathing during sleep in a reliable, non-invasive way is challenging and currently not included in sleep studies. However, it has a high clinical relevance in pediatrics, as it can negatively impact the physical and mental health of children. Since mouth breathing is an anomalous condition in the general population with only 2% prevalence in our data set, we are facing an anomaly detection problem. This type of human medical data is commonly approached with deep learning methods. However, applying multiple supervised and unsupervised machine learning methods to this anomaly detection problem showed that classic machine learning methods should also be taken into account. This paper compared deep learning and classic machine learning methods on respiratory data during sleep using a leave-one-out cross validation. This way we observed the uncertainty of the models and their performance across participants with varying signal quality and prevalence of mouth breathing. The main contribution is identifying the model with the highest clinical relevance to facilitate the diagnosis of chronic mouth breathing, which may allow more affected children to receive appropriate treatment.","PeriodicalId":55183,"journal":{"name":"Data Mining and Knowledge Discovery","volume":"60 24","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136348550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0