arXiv subjects

Massimiliano Dal Mas

Publications and source records attributed to Massimiliano Dal Mas.

16 recordsLinked to original sources

arXiv2019

Emergent Behaviors from Folksonomy Driven Interactions

To reflect the evolving knowledge on the Web this paper considers ontologies based on folksonomies according to a new concept structure called "Folksodriven" to represent folksonomies. This paper describes a research program for studying Folksodriven tags interactions leading to Folksodriven cluster behavior. The goal of the research is to understand the type of simple local interactions which produce complex and purposive group behaviors on Folksodriven tags. We describe a synthetic, bottom-up approach to studying group behavior, consisting of designing and testing a variety of social interactions and cultural scenarios with Folksodriven tags. We propose a set of basic interactions which can be used to structure and simplify the process of both designing and analyzing emergent group behaviors. The presented behavior repertories was developed and tested on a folksonomy environment.

cs.AI↗

arXiv2018

Responsive Equilibrium for Self-Adaptive Ubiquitous Interaction

This work attempts to unify two domains: the Game Theory for cooperative control systems and the Responsive Web Design, under the umbrella of crowdsourcing for information gain on Ubiquous Sytems related to different devices (as PC, Tablet, Mobile,...) This paper proposes a framework for adapting DOM objects components for a disaggregated system, which dynamically composes web pages for different kind of devices including ubiquitous/pervasive computing systems. It introduces the notions of responsive webdesign for non-cooperative Nash equilibrium proposing an algorithm (RE-SAUI) for the dynamic interface based on the game theory.

cs.HC↗

arXiv2018

Web Application for Collaborative Semantic Web Information Architecture

In this paper is analyzed the prototyping of the information visualization on a Web Application for community purposes in a collaborative environment representing an evolution of the actual social networks like Facebook, Instagram, Twitter, Linkedin, VirgilioPeople,... The intent of this work is to identify the most common features of Web App for the information visualization based on the Semantic Web and discuss how they support the user's requirements in a "collaborative" environment. A solution for the context-aware development of UI is based on "joint meaning" understood as a joint construal of the creator of the community contents and the user of the community contents thanks to the context and interface adaptation using the faced taxonomy with the Semantic Web. A proof-of concept prototype allows showing that the proposed methodological approach can also easily be applied to existing presentation components, built with different languages and/or component technologies.

cs.CY↗

arXiv2017

Digital Advertising Traffic Operation: Flow Management Analysis

In a Web Advertising Traffic Operation the Trafficking Routing Problem (TRP) consists in scheduling the management of Web Advertising (Adv) campaign between Trafficking campaigns in the most efficient way to oversee and manage relationship with partners and internal teams, managing expectations through integration and post-launch in order to ensure success for every stakeholders involved. For our own interest we did that independent research projects also through specific innovative tasks validate towards average working time declared on "specification required" by the main worldwide industry leading Advertising Agency. We present a Mixed Integer Linear Programming (MILP) formulation for end-to-end management of campaign workflow along a predetermined path and generalize it to include alternative path to oversee and manage detail-oriented relationship with partners and internal teams to achieve the goals above mentioned. To meet clients' KPIs, we consider an objective function that includes the punctuality indicators (the average waiting time and completion times) but also the main punctuality indicators (the average delay and the on time performance). Then we investigate their analytical relationships in the advertising domain through experiments based on real data from a Traffic Office. We show that the classic punctuality indicators are in contradiction with the task of reducing waiting times. We propose new indicators used for a synthesize analysis on projects or process changes for the wider team that are more sustainable, but also more relevant for stakeholders. We also show that the flow of a campaign (adv-ways) is the main bottleneck of a Traffic Office and that alternate paths cannot improve the performance indicators.

cs.SI↗

arXiv2016

FolksoDrivenCloud: an annotation and process application for social collaborative networking

In this paper we present the FolksoDriven Cloud (FDC) built on Cloud and on Semantic technologies. Cloud computing has emerged in these recent years as the new paradigm for the provision of on-demand distributed computing resources. Semantic Web can be used for relationship between different data and descriptions of services to annotate provenance of repositories on ontologies. The FDC service is composed of a back-end which submits and monitors the documents, and a user front-end which allows users to schedule on-demand operations and to watch the progress of running processes. The impact of the proposed method is illustrated on a user since its inception.

cs.CY↗

arXiv2016

Automatic Data Deformation Analysis on Evolving Folksonomy Driven Environment

The Folksodriven framework makes it possible for data scientists to define an ontology environment where searching for buried patterns that have some kind of predictive power to build predictive models more effectively. It accomplishes this through an abstractions that isolate parameters of the predictive modeling process searching for patterns and designing the feature set, too. To reflect the evolving knowledge, this paper considers ontologies based on folksonomies according to a new concept structure called "Folksodriven" to represent folksonomies. So, the studies on the transformational regulation of the Folksodriven tags are regarded to be important for adaptive folksonomies classifications in an evolving environment used by Intelligent Systems to represent the knowledge sharing. Folksodriven tags are used to categorize salient data points so they can be fed to a machine-learning system and "featurizing" the data.

cs.IR↗

arXiv2016

Digital Advertising Traffic Operation: Machine Learning for Process Discovery

In a Web Advertising Traffic Operation it's necessary to manage the day-to-day trafficking, pacing and optimization of digital and paid social campaigns. The data analyst on Traffic Operation can not only quickly provide answers but also speaks the language of the Process Manager and visually displays the discovered process problems. In order to solve a growing number of complaints in the customer service process, the weaknesses in the process itself must be identified and communicated to the department. With the help of Process Mining for the CRM data it is possible to identify unwanted loops and delays in the process. With this paper we propose a process discovery based on Machine Learning technique to automatically discover variations and detect at first glance what the problem is, and undertake corrective measures.

cs.CY↗

arXiv2015

Function of Forgetfulness for the Tedium of Oblivion on Liquidity of Ontology Matching

The shallow and fragile knowledge on the Web does not examine in depth the things: it behaves lightly. The conditions created by the Web makes our attention labile and especially fickle, it's unable to concentrate for long as we are trained to "surf" without going though never in depth. The Web also brings with it the added advantage of a nearly availability infinite knowledge but leads to a loss of the ability to retain and evaluate that knowledge within us increasing forgetfulness of knowledge. In this paper we show how the "function of forgetfulness" appears linked to tedium and oblivion of knowledge through the liquidity of ontology matching.

cs.CY↗

arXiv2014

Liquidity on Web Dynamic Network

Nowadays, the exponentially growing of the Web renders the problem of correlation among different topics of paramount importance. The proposed model can be used to study the evolution of network depicted by different topics on the web correlated by a dynamic "fluid" of tags among them. The fluid-dynamic model depicted is completely evolutive, thus it is able to describe the dynamic situation of a network at every instant of time. This overcomes the difficulties encountered by many static models. The theory permits the development of efficient numerical schemes also for very large networks. This is possible since dynamic flow at junctions is modeled in a simple and computationally convenient way (resorting to a linear programming problem). The obtained model consists of a single conservation law and is on one side simple enough to permit a complete understanding, on the other side reach enough to detect the evolution of the dynamic network.

cs.SI↗

arXiv2012

Intelligent Interface Architectures for Folksonomy Driven Structure Network

The folksonomy is the result of free personal information or assignment of tags to an object (determined by the URI) in order to find them. The practice of tagging is done in a collective environment. Folksonomies are self constructed, based on co-occurrence of definitions, rather than a hierarchical structure of the data. The downside of this was that a few sites and applications are able to successfully exploit the sharing of bookmarks. The need for tools that are able to resolve the ambiguity of the definitions is becoming urgent as the need of simple instruments for their visualization, editing and exploitation in web applications still hinders their diffusion and wide adoption. An intelligent interactive interface design for folksonomies should consider the contextual design and inquiry based on a concurrent interaction for a perceptual user interfaces. To represent folksonomies a new concept structure called "Folksodriven" is used in this paper. While it is presented the Folksodriven Structure Network (FSN) to resolve the ambiguity of definitions of folksonomy tags suggestions for the user. On this base a Human-Computer Interactive (HCI) systems is developed for the visualization, navigation, updating and maintenance of folksonomies Knowledge Bases - the FSN - through the web. System functionalities as well as its internal architecture will be introduced.

cs.HC↗

arXiv2012

Faceted Semantic Search for Personalized Social Search

Actual social networks (like Facebook, Twitter, Linkedin, ...) need to deal with vagueness on ontological indeterminacy. In this paper is analyzed the prototyping of a faceted semantic search for personalized social search using the "joint meaning" in a community environment. User researches in a "collaborative" environment defined by folksonomies can be supported by the most common features on the faceted semantic search. A solution for the context-aware personalized search is based on "joint meaning" understood as a joint construal of the creators of the contents and the user of the contents using the faced taxonomy with the Semantic Web. A proof-of concept prototype shows how the proposed methodological approach can also be applied to existing presentation components, built with different languages and/or component technologies.

cs.IR↗

arXiv2012

Elasticity on Ontology Matching of Folksodriven Structure Network

Nowadays folksonomy tags are used not just for personal organization, but for communication and sharing between people sharing their own local interests. In this paper is considered the new concept structure called "Folksodriven" to represent folksonomies. The Folksodriven Structure Network (FSN) was thought as folksonomy tags suggestions for the user on a dataset built on chosen websites - based on Natural Language Processing (NLP). Morphological changes, such as changes in folksonomy tags chose have direct impact on network connectivity (structural plasticity) of the folksonomy tags considered. The goal of this paper is on defining a base for a FSN plasticity theory to analyze. To perform such goal it is necessary a systematic mathematical analysis on deformation and fracture for the ontology matching on the FSN. The advantages of that approach could be used on a new interesting method to be employed by a knowledge management system.

cs.DL↗

arXiv2011

Cluster Analysis for a Scale-Free Folksodriven Structure Network

Folksonomy is said to provide a democratic tagging system that reflects the opinions of the general public, but it is not a classification system and it is hard to make sense of. It would be necessary to share a representation of contexts by all the users to develop a social and collaborative matching. The solution could be to help the users to choose proper tags thanks to a dynamical driven system of folksonomy that could evolve during the time. This paper uses a cluster analysis to measure a new concept of a structure called "Folksodriven", which consists of tags, source and time. Many approaches include in their goals the use of folksonomy that could evolve during time to evaluate characteristics. This paper describes an alternative where the goal is to develop a weighted network of tags where link strengths are based on the frequencies of tag co-occurrence, and studied the weight distributions and connectivity correlations among nodes in this network. The paper proposes and analyzes the network structure of the Folksodriven tags thought as folksonomy tags suggestions for the user on a dataset built on chosen websites. It is observed that the hypergraphs of the Folksodriven are highly connected and that the relative path lengths are relatively low, facilitating thus the serendipitous discovery of interesting contents for the users. Then its characteristics, Clustering Coefficient, is compared with random networks. The goal of this paper is a useful analysis of the use of folksonomies on some well known and extensive web sites with real user involvement. The advantages of the new tagging method using folksonomy are on a new interesting method to be employed by a knowledge management system. *** This paper has been accepted to the International Conference on Social Computing and its Applications (SCA 2011) - Sydney Australia, 12-14 December 2011 ***

cs.SI↗

arXiv2011

Folksodriven Structure Network

Nowadays folksonomy is used as a system derived from user-generated electronic tags or keywords that annotate and describe online content. But it is not a classification system as an ontology. To consider it as a classification system it would be necessary to share a representation of contexts by all the users. This paper is proposing the use of folksonomies and network theory to devise a new concept: a "Folksodriven Structure Network" to represent folksonomies. This paper proposed and analyzed the network structure of Folksodriven tags thought as folsksonomy tags suggestions for the user on a dataset built on chosen websites. It is observed that the Folksodriven Network has relative low path lengths checking it with classic networking measures (clustering coefficient). Experiment result shows it can facilitate serendipitous discovery of content among users. Neat examples and clear formulas can show how a "Folksodriven Structure Network" can be used to tackle ontology mapping challenges.

cs.IR↗

arXiv2011

Search for Hidden Knowledge in Collective Intelligence dealing Indeterminacy Ontology of Folksonomy with Linguistic Pragmatics and Quantum Logic

Information retrieval is not only the most frequent application executed on the Web but it is also the base of different types of applications. Considering collective intelligence of groups of individuals as a framework for evaluating and incorporating new experiences and information we often cannot retrieve such knowledge being tacit. Tacit knowledge underlies many competitive capabilities and it is hard to articulate on discrete ontology structure. It is unstructured or unorganized, and therefore remains hidden. Developing generic solutions that can find the hidden knowledge is extremely complex. Moreover this will be a great challenge for the developers of semantic technologies. This work aims to explore ways to make explicit and available the tacit knowledge hidden in the collective intelligence of a collaborative environment within organizations. The environment was defined by folksonomies supported by a faceted semantic search. Vector space model which incorporates an analogy with the mathematical apparatus of quantum theory is adopted for the representation and manipulation of the meaning of folksonomy. Vector space retrieval has been proven efficiency when there isn't a data behavioural because it bears ranking algorithms involving a small number of types of elements and few operations. A solution to find what the user has in mind when posing a query could be based on "joint meaning" understood as a joint construal of the creator of the contents and the reader of the contents. The joint meaning was proposed to deal with vagueness on ontology of folksonomy indeterminacy, incompleteness and inconsistencies on collective intelligence. A proof-of concept prototype was built for collaborative environment as evolution of the actual social networks (like Facebook, LinkedIn,..) using the information visualization on a RIA application with Semantic Web techniques and technologies.

cs.IR↗

arXiv2010

Ontology Temporal Evolution for Multi-Entity Bayesian Networks under Exogenous and Endogenous Semantic Updating

It is a challenge for any Knowledge Base reasoning to manage ubiquitous uncertain ontology as well as uncertain updating times, while achieving acceptable service levels at minimum computational cost. This paper proposes an application-independent merging ontologies for any open interaction system. A solution that uses Multi-Entity Bayesan Networks with SWRL rules, and a Java program is presented to dynamically monitor Exogenous and Endogenous temporal evolution on updating merging ontologies on a probabilistic framework for the Semantic Web.

cs.AI↗