Session identification techniques used in web usage mining

Fatima, Bahjat; Ramzan, Huma; Asghar, Sohail

doi:10.1108/oir-08-2015-0274

Cited by 10 publications

(5 citation statements)

References 27 publications

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“…Prior research has proposed various strategies to determine appropriate session boundaries, such as time-oriented heuristics, imposing a threshold on the total session duration (usually 30 minutes) or a maximum duration limit on a specific page (generally 10 minutes) (Cooley et al, 1999); navigation-based heuristics, making use of browser navigation, i.e., examining the structure of the website to identify user sessions: when two sequential logs refer to pages which are not directly connected, a new user session begins (Nadjarbashi-Noghani & Ghorbani, 2004); task-based heuristics, finding groups of semantically related search queries tackling the same task (Boldi et al, 2008;Jones & Klinkner, 2008); or employing meaningful transactions identified using a reference length approach (Fatima et al, 2016).…”

Section: Background and Related Workmentioning

confidence: 99%

“…For a web search, usually, a session is addressed as specific brief sequences of queries submitted to the web search engine by a user to address a single information need (Jansen et al, 2007), and search sessions are temporal sequences of queries issued by users (Lucchese et al, 2013). However, there have been many attempts to segment and define sessions that do not directly address the concept of user information demands but rely on the concept of similar context, topic, or temporal characteristics (Jones & Klinkner, 2008;Fatima et al, 2016).…”

Section: Background and Related Workmentioning

confidence: 99%

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Session-Based Time-Window Identification in Virtual Learning Environments

Maslennikova,

Rotelli,

Monreale

2023

Learning Analytics

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Students organize and manage their own learning time, choosing when, what, and how to study due to the flexibility of online learning. Each person has unique learning habits that define their behaviours and distinguish them from others. To investigate the temporal behaviour of students in online learning environments, we seek to identify suitable time-windows that could be used to investigate their temporal behaviour. First, we present a novel perspective for identifying different types of sessions based on individual needs. The majority of previous works address this issue by establishing an arbitrary session timeout threshold. In this paper, we propose an algorithm for determining the optimal threshold for a given session. Second, we use data-driven methods to support investigators in determining time-windows based on the identified sessions. To this end, we developed a visual tool that assists data scientists and researchers to determine the optimal settings for session identification and locating suitable time-windows.

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Section: Background and Related Workmentioning

confidence: 99%

Section: Background and Related Workmentioning

confidence: 99%

Session-Based Time-Window Identification in Virtual Learning Environments

Maslennikova,

Rotelli,

Monreale

2023

Learning Analytics

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“…In addition, he will share experiences, skills and problems afflicting him in the work environment and receive guidance from other users. User identification is necessary to set what will be accessed and for how long with the help of algorithms in a digital environment (Fatima et al , 2016).…”

Section: Theoretical B2b Knowledge Management Framework Focused On Va...mentioning

confidence: 99%

Theoretical B2B knowledge management framework focused on value co-creation

Ferenhof

Bonamigo

Rosa

et al. 2022

VJIKMS

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Purpose Knowledge is companies’ crucial asset, especially when they are inserted in continuous collaboration and value co-creation. However, problems related to knowledge may occur without proper management, which can compromise the strategic objectives associated with a business collaboration network. Given the presented gap, this study aims to propose and test a business-to-business (B2B) knowledge management (KM) framework focused on value co-creation. Therefore, this study seeks to answer the following guiding questions: what are the main elements that a KM model should present in a context of value co-creation between companies? What are the limitations? What are the advantages and disadvantages? Is there any group that would benefit most from it? Design/methodology/approach This is an exploratory study grounded on mixed methods, having a qualitative approach (systematic literature review and content analysis) followed by a quantitative approach (exploratory and confirmatory factor analysis), which grounded the proposed framework. Findings The qualitative approach grounded on the systematic literature review resulting in 38 articles that were submitted to content analysis, which resulted in six record units: active communication between the organization, employees and other stakeholders; documents and organizational knowledge stored; knowledge map; collaborative network; searching tools and database, which provided the KM elements to develop and test the proposed framework by the quantitative approach. The results have shown that the framework may assist in managing knowledge in B2B value co-creation relationships. Research limitations/implications As an exploratory study, the chosen research approach used nonprobabilistic for convenience sampling. Therefore, the results may lack generalizability. Thus, researchers are encouraged to use probabilistic sampling techniques to ensure generability. Also, more and better items should be used to upgrade the initial questionnaire, improving it and, by doing so, have a better scale. Practical implications Assuming the proposed framework’s effectiveness, company managers can use it to drive knowledge within the network of interested parties to promote cooperative products and services. In addition, due to the theoretical framework’s broad vision, it can serve as a strategic aid to leverage innovation, productivity and competitive advantage. This study also provides an initial instrument that assists in understanding KM elements, which may assist in value co-creation. Originality/value It was learned that the elements, tools, concepts and KM preconized solutions can assist in value co-creation. Considering that value assists business performance, and value co-creation is one way to enhance it, furthermore, by knowledge sharing, the value co-creation may occur in the B2B ecosystem. Also, it is the first theoretical KM framework proposed to assist companies to understand better ways that could get advantages on structuring knowledge, meaning mapping it, sharing it through a system that can retain what is needed and release it to the ones that need and have the defined access to receive it.

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“…A web usage mining method is proposed [1], this method can be applied to solve the problem of developing more accurate and efficient recommendation systems, the traditional data protection mechanism focuses on the access control and the secure transmission, which provide only security against malicious the third parties, but not the service provider, so this method can mine efficiently and intelligently data, in order to guide and track the users' usage behavior, and does main contribution in the application direction of the modern Ebusiness. A web usage mining method is proposed [11], in this method, the state-of-the-art session identification technology is used in terms of limitation, feature, and methodology, which provide a structured overview of the research development, in this technical context, the comparative experiments critically review existing session identification technology, the whole research result does main contribution in highlighting the limitation and related challenge, identifying the area where further improvement is required, in order to complement the performance of existing technology. A web usage mining method is proposed [21], in this method, an algorithm is also designed for the data cleaning and filtering using the web log dataset, this algorithm mainly complete the process of preprocessing and clustering the usage behavior, which consists of the use cases for the data cleaning and filtering, the user and session identification, in this technical context, the experiments are carried out to obtain the aggregate clustering results, through this process, two datasets of web usage log are collected and processed, so the whole research result does main contribution in the area of web usage behavior analysis.…”

Section: Related Workmentioning

confidence: 99%

Research on Key Technology of Web Hierarchical Topic Detection and Evolution Based on Behaviour Tracking Analysis

Chen

2019

INT J COMPUT COMMUN

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In the development background of today’s big data era, the research direction of Web hierarchical topic detection and evolution characterized by the semistructured or unstructured data has caught wide attention for academicians. This paper proposes an idea of Web hierarchical topic detection and evolution based on behaviour tracking analysis taking the network big data as the research object, and expounds main implementation methods, which include the instance analysis of the usage mode, the instance analysis of the seed, the set analysis of similar instance supporting the topics, the set analysis of similar instance supporting the events, the evolution analysis of the event, and expounds the algorithm of Web hierarchical topic detection and evolution based on behaviour tracking analysis. The process of experimental analysis is organized as follows, first of all, the experiment analyses the quality of topic detection, the accuracy rate with the number of instance concerned and the seed threshold variation trend, the accuracy rate with the number of instance concerned and the probability threshold variation trend, secondly, the experiment analyses the quality of topic evolution, the accuracy rate with the variation trend of parameter adjustment, the accuracy rate with the number of instance concerned and the similar threshold variation trend, finally, the experiment analyses the time consuming to solve main research problem under different method, the qualitative result of topic detection and evolution under different data set. The results of experimental analysis show the idea is feasible, verifiable and superior, which plays a major role in reconfiguring Web hierarchical topic corpus and providing an intelligent big data warehouse for the network information evolution application.

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Session identification techniques used in web usage mining

Cited by 10 publications

References 27 publications

Session-Based Time-Window Identification in Virtual Learning Environments

Session-Based Time-Window Identification in Virtual Learning Environments

Theoretical B2B knowledge management framework focused on value co-creation

Research on Key Technology of Web Hierarchical Topic Detection and Evolution Based on Behaviour Tracking Analysis

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