WUM: A Tool for Web Utilization Analysis

Spiliopoulou, Myra; Faulstich, Lukas

doi:10.1007/10704656_12

Cited by 136 publications

(100 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The query answers are ordered to reflect the number of times these community neighborhoods have been visited. [24], [25], [26], [27] proposed adapting search results based on users' history, navigational history, browsing history, or query history. There are multiple data mining techniques that can be applied to extract usage patterns from Web logs [24], [25].…”

Section: Non-authority Flow Personalizationmentioning

confidence: 99%

Efficient Ranking on Entity Graphs with Personalized Relationships

Hristidis

Raschid

2014

IEEE Trans. Knowl. Data Eng.

View full text Add to dashboard Cite

Abstract-Authority flow techniques like PageRank and ObjectRank can provide personalized ranking of typed entity-relationship graphs. There are two main ways to personalize authority flow ranking: Node-based personalization, where authority originates from a set of user-specific nodes; Edge-based personalization, where the importance of different edge types is user-specific. We propose the first approach to achieve efficient edge-based personalization using a combination of precomputation and runtime algorithms.In particular, we apply our method to ObjectRank, where a personalized weight assignment vector (WAV) assigns different weights to each edge type or relationship type. Our approach includes a repository of rankings for various WAVs. We consider the following two classes of approximation: (a) SchemaApprox is formulated as a distance minimization problem at the schema level; (b) DataApprox is a distance minimization problem at the data graph level. SchemaApprox is not robust since it does not distinguish between important and trivial edge types based on the edge distribution in the data graph. In contrast, DataApprox has a provable error bound. Both SchemaApprox and DataApprox are expensive so we develop efficient heuristic implementations, ScaleRank and PickOne respectively. Extensive experiments on the DBLP data graph show that ScaleRank provides a fast and accurate personalized authority flow ranking.

show abstract

Section: Non-authority Flow Personalizationmentioning

confidence: 99%

Efficient Ranking on Entity Graphs with Personalized Relationships

Hristidis

Raschid

2014

IEEE Trans. Knowl. Data Eng.

View full text Add to dashboard Cite

show abstract

“…In addition to episode identification, SpeedTracer makes use of referrer and agent information in the preprocessing routines to identify users and server sessions in the absence of additional client side information. The Web Utilization Miner (WUM) system [Spiliopoulou and Faulstich, 1998] provides a robust mining language in order to specify characteristics of discovered frequent paths that are interesting to the analyst. Zaiane et al (1998) have loaded Web server logs into a data cube structure in order to perform data mining as well as On-Line Analytical Processing (OLAP) activities such as roll-up and drill-down of the data.…”

Section: Web Miningmentioning

confidence: 99%

Enhancing the Website Structure by Reconciling Website

Sona¹

2012

IOSRJEN

View full text Add to dashboard Cite

show abstract

“…Discovery of navigation patterns: Spiliopoulou and Faulstich [3] present the Web Utilization Miner WUM, a mining system for discovering interesting navigation patterns in a web site. WUM prepares the web log data for mining and the language MINT mining the aggregated data according to the directives of the human expert.…”

Section: Background and Related Workmentioning

confidence: 99%

Creating User Profiles from a Command-Line Interface: A Statistical Approach

Iglesias

Ledezma

Sanchís

2009

User Modeling, Adaptation, and Personalization

View full text Add to dashboard Cite

Abstract. Knowledge about computer users is very beneficial for assisting them, predicting their future actions or detecting masqueraders. In this paper, an approach for creating and recognizing automatically the behavior profile of a user from the commands (s)he types in a commandline interface, is presented.Specifically, in this research, a computer user behavior is represented as a sequence of UNIX commands. This sequence is transformed into a distribution of relevant subsequences in order to find out a profile that defines its behavior. Then, statistical methods are used for recognizing a user from the commands (s)he types. The experiment results, using 2 different sources of UNIX command data, show that a system based on our approach can efficiently recognize a UNIX user. In addition, a comparison with a HMM-base method is done.Because a user profile usually changes constantly, we also propose a method to keep up to date the created profiles using an age-based mechanism.

show abstract

WUM: A Tool for Web Utilization Analysis

Cited by 136 publications

References 7 publications

Efficient Ranking on Entity Graphs with Personalized Relationships

Efficient Ranking on Entity Graphs with Personalized Relationships

Enhancing the Website Structure by Reconciling Website

Creating User Profiles from a Command-Line Interface: A Statistical Approach

Contact Info

Product

Resources

About