LOGPAT: A semi-automatic way to analyze hypertext navigation behavior

2003 ◽  
Vol 62 (2) ◽  
pp. 113-120 ◽  
Author(s):  
Tobias Richter ◽  
Johannes Naumann ◽  
Stephan Noller
Keyword(s):  
Data Reduction ◽  
Single Unit ◽  
Pattern Analysis ◽  
Psychological Research ◽  
Minimum Loss ◽  
Web Based ◽  
Graph Theoretic ◽  
Log Files ◽  
Log File ◽  
Source Of Information

In hypertext research, log files represent a useful source of information about users’ navigational behavior. Since log files can contain enormous amounts of data, methods for data reduction with a minimum loss of information are needed. In this paper, LOGPAT (Log file Pattern Analysis) is presented, a Web-based tool for analyzing log files. With LOGPAT, single-unit, sequential, and graph-theoretic measures (including distance matrices) for the description of user navigation can be computed. The paper gives an overview of these methods and discusses their value for psychological research on hypertext. Components and analysis options of LOGPAT are described in detail. The program’s basic options are illustrated by data from a study on learning with hypertext.

Discovering Learners Behaviour Patterns From Log Files Using LSA

2020 ◽  
Vol 18 (2) ◽  
pp. 90-113
Author(s):  
Iness Nedji Milat ◽  
Hassina Seridi ◽  
Abdelkader Moudjari
Keyword(s):  
Semantic Analysis ◽  
Direct Interaction ◽  
Learning System ◽  
Huge Amount ◽  
New Approach ◽  
Log Files ◽  
E Learning ◽  
Log File ◽  
The Relationship ◽  
Source Of Information

Recently, discovering learner behaviour has taken more attention in the field of e-learning. It aims to gain useful insights into the learning process of students despite the absence of direct interaction with teachers. In fact, the only available source of information in such environments is the log file that represents all possible interactions of learners with the e-learning system. This log file is characterised by the presence of noise, incomplete information, and a huge amount of data. In this article, a new approach based on learner trails analysis from the log file is proposed. It aims to discover the patterns of the real behaviour of learners and to determine their pedagogic orientations. The latent semantic analysis (LSA) method is used to extract the relationship between learners who have the same behaviour and to overcome the noise problem. The proposed approach has been validated using synthetic and genuine log files. The obtained results show the efficiency of the proposed method of discovering the behaviours of learners.

scholarly journals An Efficient Analytical Approach to Visualize Text-Based Event Logs for Semiconductor Equipment

2021 ◽  
Vol 11 (13) ◽  
pp. 5944
Author(s):  
Gunwoo Lee ◽  
Jongpil Jeong
Keyword(s):  
Complex System ◽  
Analytical Approach ◽  
System Behavior ◽  
File Size ◽  
Log Files ◽  
Event Logs ◽  
Hard Disk Space ◽  
Long Time ◽  
Log File ◽  
Runtime Information

Semiconductor equipment consists of a complex system in which numerous components are organically connected and controlled by many controllers. EventLog records all the information available during system processes. Because the EventLog records system runtime information so developers and engineers can understand system behavior and identify possible problems, it is essential for engineers to troubleshoot and maintain it. However, because the EventLog is text-based, complex to view, and stores a large quantity of information, the file size is very large. For long processes, the log file comprises several files, and engineers must look through many files, which makes it difficult to find the cause of the problem and therefore, a long time is required for the analysis. In addition, if the file size of the EventLog becomes large, the EventLog cannot be saved for a prolonged period because it uses a large amount of hard disk space on the CTC computer. In this paper, we propose a method to reduce the size of existing text-based log files. Our proposed method saves and visualizes text-based EventLogs in DB, making it easier to approach problems than the existing text-based analysis. We will confirm the possibility and propose a method that makes it easier for engineers to analyze log files.

scholarly journals User Identification in the Process of Web Usage Data Preprocessing

2019 ◽  
Vol 14 (09) ◽  
pp. 21 ◽  
Author(s):  
Jozef Kapusta ◽  
Michal Munk ◽  
Dominik Halvoník ◽  
Martin Drlík
Keyword(s):  
User Behavior ◽  
Web Server ◽  
Web Browser ◽  
Ip Address ◽  
User Session ◽  
Log Files ◽  
The Us ◽  
Log File ◽  
Default Form

If we are talking about user behavior analytics, we have to understand what the main source of valuable information is. One of these sources is definitely a web server. There are multiple places where we can extract the necessary data. The most common ways are to search for these data in access log, error log, custom log files of web server, proxy server log file, web browser log, browser cookies etc. A web server log is in its default form known as a Common Log File (W3C, 1995) and keeps information about IP address; date and time of visit; ac-cessed and referenced resource. There are standardized methodologies which contain several steps leading to extract new knowledge from provided data. Usu-ally, the first step is in each one of them to identify users, users’ sessions, page views, and clickstreams. This process is called pre-processing. Main goal of this stage is to receive unprocessed web server log file as input and after processing outputs meaningful representations which can be used in next phase. In this pa-per, we describe in detail user session identification which can be considered as most important part of data pre-processing. Our paper aims to compare the us-er/session identification using the STT with the identification of user/session us-ing cookies. This comparison was performed concerning the quality of the se-quential rules generated, i.e., a comparison was made regarding generation useful, trivial and inexplicable rules.

scholarly journals A New Remote Guided Method for Supervised Web-Based Cognitive Testing to Ensure High Quality Data

2021 ◽  
Author(s):  
Victoria Leong ◽  
Kausar Raheel ◽  
Sim Jia Yi ◽  
Kriti Kacker ◽  
Vasilis M. Karlaftis ◽  
...  
Keyword(s):  
Data Quality ◽  
Response Times ◽  
Psychological Research ◽  
Cognitive Testing ◽  
Quality Data ◽  
High Quality ◽  
Online Data ◽  
Test Environment ◽  
Web Based ◽  
Cognitive Data

Background. The global COVID-19 pandemic has triggered a fundamental reexamination of how human psychological research can be conducted both safely and robustly in a new era of digital working and physical distancing. Online web-based testing has risen to the fore as a promising solution for rapid mass collection of cognitive data without requiring human contact. However, a long-standing debate exists over the data quality and validity of web-based studies. Here, we examine the opportunities and challenges afforded by the societal shift toward web-based testing, highlight an urgent need to establish a standard data quality assurance framework for online studies, and develop and validate a new supervised online testing methodology, remote guided testing (RGT). Methods. A total of 85 healthy young adults were tested on 10 cognitive tasks assessing executive functioning (flexibility, memory and inhibition) and learning. Tasks were administered either face-to-face in the laboratory (N=41) or online using remote guided testing (N=44), delivered using identical web-based platforms (CANTAB, Inquisit and i-ABC). Data quality was assessed using detailed trial-level measures (missed trials, outlying and excluded responses, response times), as well as overall task performance measures. Results. The results indicated that, across all measures of data quality and performance, RGT data was statistically-equivalent to data collected in person in the lab. Moreover, RGT participants out-performed the lab group on measured verbal intelligence, which could reflect test environment differences, including possible effects of mask-wearing on communication. Conclusions. These data suggest that the RGT methodology could help to ameliorate concerns regarding online data quality and - particularly for studies involving high-risk or rare cohorts - offer an alternative for collecting high-quality human cognitive data without requiring in-person physical attendance.

scholarly journals Fascinatin’ Rhythm – and Pauses in Translators’ Cognitive Processes

2018 ◽  
pp. 29
Author(s):  
Ricardo Muñoz Martín ◽  
Celia Martín de Leon
Keyword(s):  
Problem Solving ◽  
Cognitive Processes ◽  
Sustained Attention ◽  
Initial Phase ◽  
Lower Threshold ◽  
Log Files ◽  
Information Searches ◽  
Log File

The Monitor Model fosters a view of translating where two mind modes stand out and alternate when trying to render originals word-by-word by default: shallow, uneventful processing vs problem solving. Research may have been biased towards problem solving, often operationalized with a pause of, or above, 3 seconds. This project analyzed 16 translation log files by four informants from four originals. A baseline minimal pause of 200 ms was instrumental to calculate two individual thresholds for each log file: (a) A low one – 1.5 times the median pause within words – and (b) a high one – 3 times the median pause between words. Pauses were then characterized as short (between 200 ms and the lower threshold), mid, and long (above the higher threshold, chunking the recorded activities in the translation task into task segments), and assumed to respond to different causes. Weak correlations between short, mid and long pauses were found, hinting at possible different cognitive processes. Inferred processes did not fall neatly into categories depending on the length of possibly associated pauses. Mid pauses occurred more often than long pauses between sentences and paragraphs, and they also more often flanked information searches and even problem-solving instances. Chains of proximal mid pauses marked cases of potential hesitations. Task segments tended to happen within 4–8 minute cycles, nested in a possible initial phase for contextualization, followed by long periods of sustained attention. We found no evidence for problem-solving thresholds, and no trace of behavior supporting the Monitor Model. 

scholarly journals Ising formulations of some graph-theoretic problems in psychological research: models and methods

2020 ◽  
Author(s):  
Michael Brusco ◽  
Clintin Davis-Stober ◽  
Douglas Steinley
Keyword(s):  
Paired Comparison ◽  
Psychological Research ◽  
Directed Acyclic Graphs ◽  
Spin Model ◽  
Mathematical Psychology ◽  
Linear Ordering ◽  
Spin Models ◽  
Graph Theoretic ◽  
Algorithm Efficiency ◽  
Ising Spin

It is well known that many NP-hard and NP-complete graph-theoretic problems can be formulated and solved as Ising spin models. We discuss several problems that have a particular history in mathematical psychology, most notably max-cut clustering, graph coloring, a linear ordering problem related to paired comparison ranking and directed acyclic graphs, and the problem of finding a minimum subset of points necessary to contain another point within a convex hull. New Ising spin models are presented for the latter two problems. In addition, we provide MATLAB software programs for obtaining solutions via enumeration of all spin ensembles (when computationally feasible) and simulated annealing. Although we are not advocating that the Ising spin model is the preferred approach for formulation and solution of graph-theoretic problems on conventional digital computers, it does provide a unifying framework for these problems. Moreover, recent progress in the development of quantum computing architecture has shown that Ising spin models can afford enormous improvements in algorithm efficiency when implemented on these platforms, which may ultimately lead to widespread use of the methodology in the future.

A New Remote Guided Method for Supervised Web-Based Cognitive Testing to Ensure High Quality Data (Preprint)

2021 ◽  
Author(s):  
Victoria Leong ◽  
Kausar Raheel ◽  
Jia Yi Sim ◽  
Kriti Kacker ◽  
Vasilis M Karlaftis ◽  
...  
Keyword(s):  
Data Quality ◽  
Response Times ◽  
Psychological Research ◽  
Cognitive Testing ◽  
Quality Data ◽  
High Quality ◽  
Online Data ◽  
Test Environment ◽  
Web Based ◽  
Cognitive Data

BACKGROUND The global COVID-19 pandemic has triggered a fundamental reexamination of how human psychological research can be conducted both safely and robustly in a new era of digital working and physical distancing. Online web-based testing has risen to the fore as a promising solution for rapid mass collection of cognitive data without requiring human contact. However, a long-standing debate exists over the data quality and validity of web-based studies. OBJECTIVE Here, we examine the opportunities and challenges afforded by the societal shift toward web-based testing, highlight an urgent need to establish a standard data quality assurance framework for online studies, and develop and validate a new supervised online testing methodology, remote guided testing (RGT). METHODS A total of 85 healthy young adults were tested on 10 cognitive tasks assessing executive functioning (flexibility, memory and inhibition) and learning. Tasks were administered either face-to-face in the laboratory (N=41) or online using remote guided testing (N=44), delivered using identical web-based platforms (CANTAB, Inquisit and i-ABC). Data quality was assessed using detailed trial-level measures (missed trials, outlying and excluded responses, response times), as well as overall task performance measures. RESULTS The results indicated that, across all measures of data quality and performance, RGT data was statistically-equivalent to data collected in person in the lab. Moreover, RGT participants out-performed the lab group on measured verbal intelligence, which could reflect test environment differences, including possible effects of mask-wearing on communication. CONCLUSIONS These data suggest that the RGT methodology could help to ameliorate concerns regarding online data quality and - particularly for studies involving high-risk or rare cohorts - offer an alternative for collecting high-quality human cognitive data without requiring in-person physical attendance. CLINICALTRIAL N.A.

Development of Secured Log Management System Over Blockchain Technology

2021 ◽  
pp. 230-235
Author(s):  
Sagar Shankar Rajebhosale ◽  
Mohan Chandrabhan Nikam
Keyword(s):  
Data Storage ◽  
Complete Solution ◽  
Extended Period ◽  
Vital Role ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Blockchain Technology ◽  
Log Files ◽  
Log Management ◽  
Log File

A log is a record of events that happens within an organization containing systems and networks. These logs are very important for any organization, because a log file will able to record all user activities. Due to this, log files play a vital role and contain sensitive information, and therefore security should be a high priority. It is very important to the proper functioning of any organization, to securely maintain log records over an extended period of time. So, management and maintenance of logs is a very difficult task. However, deploying such a system for high security and privacy of log records may be overhead for an organization and require additional costs. Many techniques have been designed for security of log records. The alternative solution for maintaining log records is using Blockchain technology. A blockchain will provide security of the log files. Log files over a Blockchain environment leads to challenges with a decentralized storage of log files. This article proposes a secured log management over Blockchain and the use of cryptographic algorithms for dealing the issues to access a data storage. This proposed technology may be one complete solution to the secure log management problem.

Sign in / Sign up

Export Citation Format

Share Document