Abstract: In this paper, we conduct a systematic survey of urban communities in Lithuania to evaluate their potential to co-create collective intelligence or “civic intelligence” applying Digital Co-creation Index methodology that includes different socio-technological indicators. Civic intelligence is a form of collective intelligence that refers to the group’s capacity to perceive societal problems and to address them effectively. The research focuses on evaluation of diverse organizational designs that increase efficient collective performance. The current scientific project advanced the state of the art by evaluating the basic preconditions in the urban communities through which the collective intelligence is being co-created under the systemic manner. The research subject is the “bottom up” digital enabled urban platforms, initiated by Lithuanian public organizations, civic movements or business entities. The web-based monitoring results obtained by applying a social indices calculation methodology and Pearson correlation analysis provided the information about the potential and limits of the urban communities and what possible changes need to be implemented to overcome the limitations.
Abstract: Recent progress in the next generation of automobile
technology is geared towards incorporating information technology
into cars. Collectively called smart cars are bringing intelligence to
cars that provides comfort, convenience and safety. A branch of smart
cars is connected-car system. The key concept in connected-cars is the
sharing of driving information among cars through decentralized
manner enabling collective intelligence. This paper proposes a
foundation of the information model that is necessary to define the
driving information for smart-cars. Road conditions are modeled
through a unique data structure that unambiguously represent the time
variant traffics in the streets. Additionally, the modeled data structure
is exemplified in a navigational scenario and usage using UML.
Optimal driving route searching is also discussed using the proposed
data structure in a dynamically changing road conditions.
Abstract: Traditional document representation for classification
follows Bag of Words (BoW) approach to represent the term weights.
The conventional method uses the Vector Space Model (VSM) to
exploit the statistical information of terms in the documents and they
fail to address the semantic information as well as order of the terms
present in the documents. Although, the phrase based approach
follows the order of the terms present in the documents rather than
semantics behind the word. Therefore, a semantic concept based
approach is used in this paper for enhancing the semantics by
incorporating the ontology information. In this paper a novel method
is proposed to forecast the intraday stock market price directional
movement based on the sentiments from Twitter and money control
news articles. The stock market forecasting is a very difficult and
highly complicated task because it is affected by many factors such
as economic conditions, political events and investor’s sentiment etc.
The stock market series are generally dynamic, nonparametric, noisy
and chaotic by nature. The sentiment analysis along with wisdom of
crowds can automatically compute the collective intelligence of
future performance in many areas like stock market, box office sales
and election outcomes. The proposed method utilizes collective
sentiments for stock market to predict the stock price directional
movements. The collective sentiments in the above social media have
powerful prediction on the stock price directional movements as
up/down by using Granger Causality test.
Abstract: “Web of Trust" is one of the recognized goals for
Web 2.0. It aims to make it possible for the people to take
responsibility for what they publish on the web, including
organizations, businesses and individual users. These objectives,
among others, drive most of the technologies and protocols recently
standardized by the governing bodies. One of the great advantages of
Web infrastructure is decentralization of publication. The primary
motivation behind Web 2.0 is to assist the people to add contents for
Collective Intelligence (CI) while providing mechanisms to link
content with people for evaluations and accountability of
information. Such structure of contents will interconnect users and
contents so that users can use contents to find participants and vice
versa. This paper proposes conceptual information storage and
linking model, based on decentralized information structure, that
links contents and people together. The model uses FOAF, Atom,
RDF and RDFS and can be used as a blueprint to develop Web 2.0
applications for any e-domain. However, primary target for this
paper is online trust evaluation domain. The proposed model targets
to assist the individuals to establish “Web of Trust" in online trust
domain.
Abstract: Biological evolution has generated a rich variety of
successful solutions; from nature, optimized strategies can be
inspired. One interesting example is the ant colonies, which are able
to exhibit a collective intelligence, still that their dynamic is simple.
The emergence of different patterns depends on the pheromone trail,
leaved by the foragers. It serves as positive feedback mechanism for
sharing information.
In this paper, we use the dynamic of TASEP as a model of
interaction at a low level of the collective environment in the ant-s
traffic flow. This work consists of modifying the movement rules of
particles “ants" belonging to the TASEP model, so that it adopts with
the natural movement of ants. Therefore, as to respect the constraints
of having no more than one particle per a given site, and in order to
avoid collision within a bidirectional circulation, we suggested two
strategies: decease strategy and waiting strategy. As a third work
stage, this is devoted to the study of these two proposed strategies-
stability. As a final work stage, we applied the first strategy to the
whole environment, in order to get to the emergence of traffic flow,
which is a way of learning.