Tree-Antimagicness of Web Graphs and Their Disjoint Union

In graph theory, the graph labeling is the assignment of labels (represented by integers) to edges and/or vertices of a graph. For a graph G=V,E, with vertex set V and edge set E, a function from V to a set of labels is called a vertex labeling of a graph, and the graph with such a function defined is called a vertex-labeled graph. Similarly, an edge labeling is a function of E to a set of labels, and in this case, the graph is called an edge-labeled graph. In this research article, we focused on studying super ad,d-T4,2-antimagic labeling of web graphs W2,n and isomorphic copies of their disjoint union.

An Hybrid Approach for Suitable Content Navigation Based on Weighted Clustering for online users

Due to exponential growth of several contents whichis created on the Web, Recommendation procedures need to bedeveloped is becoming critical. Inestimable diverse classes ofrecommendations are done on the Web each day, which includespictures, song, imageries, files recommendations, suggestion ofqueries, recommendation of tags, etc. No restriction that whatcategories of data sources are handled for the recommendations,basically these sources of data can be demonstrated in thecustom of numerous categories of graphs. This paper providedthe Common structure on mining the Web graphs forReferences using a hybrid method for appropriate contentnavigation built on weighted clustering for online users. First werecommend a collaborative filtering method to acquire theappropriate content from web records and creating theweighted clusters of related items for the user created queries.Secondly centered on the click through data study we achievethe interests and hidden semantic associations betweencustomers and queries also queries and clicked Web data. Andbased on this clickthrough information the bipartite graph willbe produced, which represents the relationship amongst thequeries and URLs. Lastly we recommend a new querysuggestion standard, personalized query recommendationcreated on weighted clustering for online users.

What an entangled Web we weave: An information-centric approach to socio-technical systems

Motivated by the increasing amount of voices who ask for careful consideration of what context-rich data analysis methods can tell us about the activities of human collectives, we contribute an argumentation that employs a dialectic of literature on the philosophy of truth and science as well as analytical methods for the study of information diffusion, Web graphs and social networks in order to make a case for changing the current view to the actions of human collectives in the digital. We strengthen our meta argument by a case study about one particular method that breaks with the causality assumption that is inherent in many of today’s methods and allows to capture novel dimensions of complexity of information sharing from a macroscopic cross-system perspective. We discuss whether this kind of analysis may generically suit to underpin the field of socio-technical systems with a novel information-centric theory.