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: The use of eXtensible Markup Language (XML) in
web, business and scientific databases lead to the development of
methods, techniques and systems to manage and analyze XML data.
Semi-structured documents suffer due to its heterogeneity and
dimensionality. XML structure and content mining represent
convergence for research in semi-structured data and text mining. As
the information available on the internet grows drastically, extracting
knowledge from XML documents becomes a harder task. Certainly,
documents are often so large that the data set returned as answer to a
query may also be very big to convey the required information. To
improve the query answering, a Semantic Tree Based Association
Rule (STAR) mining method is proposed. This method provides
intentional information by considering the structure, content and the
semantics of the content. The method is applied on Reuter’s dataset
and the results show that the proposed method outperforms well.
Abstract: An analysis of word semantics focusing on the invariance of advanced imagery in several pressing problems. Interest in the language of imagery is caused by the introduction, in the linguistics sphere, of a new paradigm, the center of which is the personality of the speaker (the subject of the language). Particularly noteworthy is the question of the place of the image when discussing the lexical, phraseological values and the relationship of imagery and metaphors. In part, the formation of a metaphor, as an interaction between two intellective entities, occurs at a cognitive level, and it is the category of the image, having cognitive roots, which aides in the correct interpretation of the results of this process on the lexical-semantic level.
Abstract: To achieve competitive advantage nowadays, most of
the industrial companies are considering that success is sustained to
great product development. That is to manage the product throughout
its entire lifetime ranging from design, manufacture, operation and
destruction. Achieving this goal requires a tight collaboration
between partners from a wide variety of domains, resulting in various
product data types and formats, as well as different software tools. So
far, the lack of a meaningful unified representation for product data
semantics has slowed down efficient product development. This
paper proposes an ontology based approach to enable such semantic
interoperability. Generic and extendible product ontology is
described, gathering main concepts pertaining to the mechanical field
and the relations that hold among them. The ontology is not
exhaustive; nevertheless, it shows that such a unified representation
is possible and easily exploitable. This is illustrated thru a case study
with an example product and some semantic requests to which the
ontology responds quite easily. The study proves the efficiency of
ontologies as a support to product data exchange and information
sharing, especially in product development environments where
collaboration is not just a choice but a mandatory prerequisite.
Abstract: Abai Kunanbayev (1845-1904) was a great Kazakh
poet, composer and philosopher. Abai's main contribution to Kazakh
culture and folklore lies in his poetry, which expresses great
nationalism and grew out of Kazakh folk culture. Before him, most
Kazakh poetry was oral, echoing the nomadic habits of the people of
the Kazakh steppes. We want to introduce to abroad our country, its
history, tradition and culture. We can introduce it only through
translations. Only by reading the Kazakh works can foreign people
know who are kazakhs, the style of their life, their thoughts and so
on. All information comes only through translation. The main
requirement to a good translation is that it should be natural or that it
should read as smoothly as the original. Literary translation should
be adequate, should follow the original to the fullest. Translators
have to be loyal to original text, they shouldn-t give the way to
liberty.
Abstract: Natural language processing systems pose a unique
challenge for software architectural design as system complexity has
increased continually and systems cannot be easily constructed from
loosely coupled modules. Lexical, syntactic, semantic, and pragmatic
aspects of linguistic information are tightly coupled in a manner that
requires separation of concerns in a special way in design,
implementation and maintenance. An aspect oriented software
architecture is proposed in this paper after critically reviewing
relevant architectural issues. For the purpose of this paper, the
syntactic aspect is characterized by an augmented context-free
grammar. The semantic aspect is composed of multiple perspectives
including denotational, operational, axiomatic and case frame
approaches. Case frame semantics matured in India from deep
thematic analysis. It is argued that lexical, syntactic, semantic and
pragmatic aspects work together in a mutually dependent way and
their synergy is best represented in the aspect oriented approach. The
software architecture is presented with an augmented Unified
Modeling Language.
Abstract: Chinese Idioms are a type of traditional Chinese idiomatic
expressions with specific meanings and stereotypes structure
which are widely used in classical Chinese and are still common in
vernacular written and spoken Chinese today. Currently, Chinese
Idioms are retrieved in glossary with key character or key word in
morphology or pronunciation index that can not meet the need of
searching semantically. OCIRS is proposed to search the desired
idiom in the case of users only knowing its meaning without any key
character or key word. The user-s request in a sentence or phrase will
be grammatically analyzed in advance by word segmentation, key
word extraction and semantic similarity computation, thus can be
mapped to the idiom domain ontology which is constructed to provide
ample semantic relations and to facilitate description logics-based
reasoning for idiom retrieval. The experimental evaluation shows that
OCIRS realizes the function of searching idioms via semantics, obtaining
preliminary achievement as requested by the users.
Abstract: Graph transformation has recently become more and
more popular as a general visual modeling language to formally state
the dynamic semantics of the designed models. Especially, it is a
very natural formalism for languages which basically are graph (e.g.
UML). Using this technique, we present a highly understandable yet
precise approach to formally model and analyze the behavioral
semantics of UML 2.0 Activity diagrams. In our proposal, AGG is
used to design Activities, then using our previous approach to model
checking graph transformation systems, designers can verify and
analyze designed Activity diagrams by checking the interesting
properties as combination of graph rules and LTL (Linear Temporal
Logic) formulas on the Activities.
Abstract: This Paper presents an on-going research in the area of Model-Driven Engineering (MDE). The premise is that UML is too unwieldy to serve as the basis for model-driven engineering. We need a smaller, simpler notation with a cleaner semantics. We propose some ideas for a simpler notation with a clean semantics. The result is known as μML, or the Micro-Modelling Language.
Abstract: One major difficulty that faces developers of
concurrent and distributed software is analysis for concurrency based
faults like deadlocks. Petri nets are used extensively in the
verification of correctness of concurrent programs. ECATNets [2] are
a category of algebraic Petri nets based on a sound combination of
algebraic abstract types and high-level Petri nets. ECATNets have
'sound' and 'complete' semantics because of their integration in
rewriting logic [12] and its programming language Maude [13].
Rewriting logic is considered as one of very powerful logics in terms
of description, verification and programming of concurrent systems.
We proposed in [4] a method for translating Ada-95 tasking
programs to ECATNets formalism (Ada-ECATNet). In this paper,
we show that ECATNets formalism provides a more compact
translation for Ada programs compared to the other approaches based
on simple Petri nets or Colored Petri nets (CPNs). Such translation
doesn-t reduce only the size of program, but reduces also the number
of program states. We show also, how this compact Ada-ECATNet
may be reduced again by applying reduction rules on it. This double
reduction of Ada-ECATNet permits a considerable minimization of
the memory space and run time of corresponding Maude program.
Abstract: It has been recognized that due to the autonomy and
heterogeneity, of Web services and the Web itself, new approaches
should be developed to describe and advertise Web services. The
most notable approaches rely on the description of Web services
using semantics. This new breed of Web services, termed semantic
Web services, will enable the automatic annotation, advertisement,
discovery, selection, composition, and execution of interorganization
business logic, making the Internet become a common
global platform where organizations and individuals communicate
with each other to carry out various commercial activities and to
provide value-added services. This paper deals with two of the
hottest R&D and technology areas currently associated with the Web
– Web services and the semantic Web. It describes how semantic
Web services extend Web services as the semantic Web improves the
current Web, and presents three different conceptual approaches to
deploying semantic Web services, namely, WSDL-S, OWL-S, and
WSMO.
Abstract: For best collaboration, Asynchronous tools and particularly the discussion forums are the most used thanks to their flexibility in terms of time. To convey only the messages that belong to a theme of interest of the tutor in order to help him during his tutoring work, use of a tool for classification of these messages is indispensable. For this we have proposed a semantics classification tool of messages of a discussion forum that is based on LSA (Latent Semantic Analysis), which includes a thesaurus to organize the vocabulary. Benefits offered by formal ontology can overcome the insufficiencies that a thesaurus generates during its use and encourage us then to use it in our semantic classifier. In this work we propose the use of some functionalities that a OWL ontology proposes. We then explain how functionalities like “ObjectProperty", "SubClassOf" and “Datatype" property make our classification more intelligent by way of integrating new terms. New terms found are generated based on the first terms introduced by tutor and semantic relations described by OWL formalism.
Abstract: Word sense disambiguation is one of the most important open problems in natural language processing applications such as information retrieval and machine translation. Many approach strategies can be employed to resolve word ambiguity with a reasonable degree of accuracy. These strategies are: knowledgebased, corpus-based, and hybrid-based. This paper pays attention to the corpus-based strategy that employs an unsupervised learning method for disambiguation. We report our investigation of Latent Semantic Indexing (LSI), an information retrieval technique and unsupervised learning, to the task of Thai noun and verbal word sense disambiguation. The Latent Semantic Indexing has been shown to be efficient and effective for Information Retrieval. For the purposes of this research, we report experiments on two Thai polysemous words, namely /hua4/ and /kep1/ that are used as a representative of Thai nouns and verbs respectively. The results of these experiments demonstrate the effectiveness and indicate the potential of applying vector-based distributional information measures to semantic disambiguation.
Abstract: The objective of the paper was to understand the use
of an important element of design, namely color in a Semiotic
system. Semiotics is the study of signs and sign processes, it is often
divided into three branches namely (i) Semantics that deals with the
relation between signs and the things to which they refer to mean, (ii)
Syntactics which addresses the relations among signs in formal
structures and (iii) Pragmatics that relates between signs and its
effects on they have on the people who use them to create a plan for
an object or a system referred to as design. Cubism with its versatility
was the key design tool prevalent across the 20th century. In order to
analyze the user's understanding of interaction and appreciation of
color through the movement of Cubism, an exercise was undertaken
in Dept. of Design, IIT Guwahati. This included tasks to design a
composition using color and sign process to the theme 'Between the
Lines' on a given tessellation where the users relate their work to the
world they live in, which in this case was the college campus of IIT
Guwahati. The findings demonstrate impact of the key design
element color on the principles of visual perception based on image
analysis of specific compositions.
Abstract: Service discovery is a very important component of Service Oriented Architectures (SOA). This paper presents two alternative approaches to customise the query results of private service registry such as Universal Description, Discovery and Integration (UDDI). The customisation is performed based on some pre-defined and/or real-time changing parameters. This work identifies the requirements, designs and additional mechanisms that must be applied to UDDI in order to support this customisation capability. We also detail the implements of the approaches and examine its performance and scalability. Based on our experimental results, we conclude that both approaches can be used to customise registry query results, but by storing personalization parameters in external resource will yield better performance and but less scalable when size of query results increases. We believe these approaches when combined with semantics enabled service registry will enhance the service discovery methods within a private UDDI registry environment.
Abstract: A key aspect of the design of any software system is
its architecture. An architecture description provides a formal model
of the architecture in terms of components and connectors and how
they are composed together. COSA (Component-Object based
Software Structures), is based on object-oriented modeling and
component-based modeling. The model improves the reusability by
increasing extensibility, evolvability, and compositionality of the
software systems. This paper presents the COSA modelling tool
which help architects the possibility to verify the structural coherence
of a given system and to validate its semantics with COSA approach.
Abstract: With the advent of emerging personal computing paradigms such as ubiquitous and mobile computing, Web contents are becoming accessible from a wide range of mobile devices. Since these devices do not have the same rendering capabilities, Web contents need to be adapted for transparent access from a variety of client agents. Such content adaptation results in better rendering and faster delivery to the client device. Nevertheless, Web content adaptation sets new challenges for semantic markup. This paper presents an advanced components platform, called MorfeoSMC, enabling the development of mobility applications and services according to a channel model based on Services Oriented Architecture (SOA) principles. It then goes on to describe the potential for integration with the Semantic Web through a novel framework of external semantic annotation of mobile Web contents. The role of semantic annotation in this framework is to describe the contents of individual documents themselves, assuring the preservation of the semantics during the process of adapting content rendering, as well as to exploit these semantic annotations in a novel user profile-aware content adaptation process. Semantic Web content adaptation is a way of adding value to and facilitates repurposing of Web contents (enhanced browsing, Web Services location and access, etc).
Abstract: Model mapping and transformation are important processes in high level system abstractions, and form the cornerstone of model-driven architecture (MDA) techniques. Considerable research in this field has devoted attention to static system abstraction, despite the fact that most systems are dynamic with high frequency changes in behavior. In this paper we provide an overview of work that has been done with regard to behavior model mapping and transformation, based on: (1) the completeness of the platform independent model (PIM); (2) semantics of behavioral models; (3) languages supporting behavior model transformation processes; and (4) an evaluation of model composition to effect the best approach to describing large systems with high complexity.
Abstract: The inherent flexibilities of XML in both structure
and semantics makes mining from XML data a complex task with
more challenges compared to traditional association rule mining in
relational databases. In this paper, we propose a new model for the
effective extraction of generalized association rules form a XML
document collection. We directly use frequent subtree mining
techniques in the discovery process and do not ignore the tree
structure of data in the final rules. The frequent subtrees based on the
user provided support are split to complement subtrees to form the
rules. We explain our model within multi-steps from data preparation
to rule generation.
Abstract: To analyze the behavior of Petri nets, the accessibility
graph and Model Checking are widely used. However, if the
analyzed Petri net is unbounded then the accessibility graph becomes
infinite and Model Checking can not be used even for small Petri
nets. ECATNets [2] are a category of algebraic Petri nets. The main
feature of ECATNets is their sound and complete semantics based on
rewriting logic [8] and its language Maude [9]. ECATNets analysis
may be done by using techniques of accessibility analysis and Model
Checking defined in Maude. But, these two techniques supported by
Maude do not work also with infinite-states systems. As a category
of Petri nets, ECATNets can be unbounded and so infinite systems.
In order to know if we can apply accessibility analysis and Model
Checking of Maude to an ECATNet, we propose in this paper an
algorithm allowing the detection if the ECATNet is bounded or not.
Moreover, we propose a rewriting logic based tool implementing this
algorithm. We show that the development of this tool using the
Maude system is facilitated thanks to the reflectivity of the rewriting
logic. Indeed, the self-interpretation of this logic allows us both the
modelling of an ECATNet and acting on it.