Search results for: Hierarchical Value Map.

Authors: Rozilawati Binti Dollah, Masaki Aono

Abstract:

Classifying biomedical literature is a difficult and challenging task, especially when a large number of biomedical articles should be organized into a hierarchical structure. In this paper, we present an approach for classifying a collection of biomedical text abstracts downloaded from Medline database with the help of ontology alignment. To accomplish our goal, we construct two types of hierarchies, the OHSUMED disease hierarchy and the Medline abstract disease hierarchies from the OHSUMED dataset and the Medline abstracts, respectively. Then, we enrich the OHSUMED disease hierarchy before adapting it to ontology alignment process for finding probable concepts or categories. Subsequently, we compute the cosine similarity between the vector in probable concepts (in the “enriched" OHSUMED disease hierarchy) and the vector in Medline abstract disease hierarchies. Finally, we assign category to the new Medline abstracts based on the similarity score. The results obtained from the experiments show the performance of our proposed approach for hierarchical classification is slightly better than the performance of the multi-class flat classification.

Keywords: Biomedical literature, hierarchical text classification, ontology alignment, text mining.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2010

Authors: Zulkeflee Kusin, Mohamad Shanudin Zakaria

Abstract:

Hierarchical Mobile IPv6 (HMIPv6) was designed to support IP micro-mobility management in the Next Generation Networks (NGN) framework. The main design behind this protocol is the usage of Mobility Anchor Point (MAP) located at any level router of network to support hierarchical mobility management. However, the distance MAP selection in HMIPv6 causes MAP overloaded and increase frequent binding update as the network grows. Therefore, to address the issue in designing MAP selection scheme, we propose a dynamic load control mechanism integrates with a speed detection mechanism (DMS-DLC). From the experimental results we obtain that the proposed scheme gives better distribution in MAP load and increase handover speed.

Keywords: Dynamic load control, HMIPv6, Mobility AnchorPoint, MAP selection scheme

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1800

Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

Abstract:

This paper presents an unsupervised color image segmentation method. It is based on a hierarchical analysis of 2-D histogram in RGB color space. This histogram minimizes storage space of images and thus facilitates the operations between them. The improved segmentation approach shows a better identification of objects in a color image and, at the same time, the system is fast.

Keywords: Image segmentation, hierarchical analysis, 2-D histogram, Classification.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1626

Authors: Mohammad Hasan Raouf, Ahmad Rouhani, Mohammad Abedini, Ebrahim Rasooli Anarmarzi

Abstract:

In this paper the application of a hierarchical fuzzy system (HFS) based on MPSS and SVC in multi-machine environment is studied. Also the effect of communication lines active power variance signal between two ΔP_Tie-line regions, as one of the inputs of hierarchical fuzzy multi-input PSS and SVC (HFMPSS & SVC), on the increase of low frequency oscillation damping is examined. In the MPSS, to have better efficiency an auxiliary signal of reactive power deviation (ΔQ) is added with ΔP+ Δω input type PSS. The number of rules grows exponentially with the number of variables in a classic fuzzy system. To reduce the number of rules the HFS consists of a number of low-dimensional fuzzy systems in a hierarchical structure. Phasor model of SVC is described and used in this paper. The performances of MPSS and ΔP_Tie-line based HFMPSS and also the proposed method in damping inter-area mode of oscillation are examined in response to disturbances. The efficiency of the proposed model is examined by simulating a four-machine power system. Results show that the proposed method is performing satisfactorily within the whole range of disturbances and reduces the cost of system.

Keywords: Communication lines active power variance signal, Hierarchical fuzzy system (HFS), Multi-input power system stabilizer (MPSS), Static VAR compensator (SVC).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1670

Authors: Maythapolnun Athimethphat, Boontarika Lerteerawong

Abstract:

There are several approaches for handling multiclass classification. Aside from one-against-one (OAO) and one-against-all (OAA), hierarchical classification technique is also commonly used. A binary classification tree is a hierarchical classification structure that breaks down a k-class problem into binary sub-problems, each solved by a binary classifier. In each node, a set of classes is divided into two subsets. A good class partition should be able to group similar classes together. Many algorithms measure similarity in term of distance between class centroids. Classes are grouped together by a clustering algorithm when distances between their centroids are small. In this paper, we present a binary classification tree with tuned observation-based clustering (BCT-TOB) that finds a class partition by performing clustering on observations instead of class centroids. A merging step is introduced to merge any insignificant class split. The experiment shows that performance of BCT-TOB is comparable to other algorithms.

Keywords: multiclass classification, hierarchical classification, binary classification tree, clustering, observation-based clustering

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1730

Authors: Jin Myoung Kim, Tae Ho Cho

Abstract:

Wireless Sensor networks have a wide spectrum of civil and military applications that call for secure communication such as the terrorist tracking, target surveillance in hostile environments. For the secure communication in these application areas, we propose a method for generating a hierarchical key structure for the efficient group key management. In this paper, we apply A* algorithm in generating a hierarchical key structure by considering the history data of the ratio of addition and eviction of sensor nodes in a location where sensor nodes are deployed. Thus generated key tree structure provides an efficient way of managing the group key in terms of energy consumption when addition and eviction event occurs. A* algorithm tries to minimize the number of messages needed for group key management by the history data. The experimentation with the tree shows efficiency of the proposed method.

Keywords: Heuristic search, key management, security, sensor network.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1683

Authors: Gideon Avigad, Amiram Moshaiov, Neima Brauner

Abstract:

An IEC technique is described for a multi-objective search of conceptual solutions. The survivability of solutions is influenced by both model-based fitness and subjective human preferences. The concepts- preferences are articulated via a hierarchy of sub-concepts. The suggested method produces an objectivesubjective front. Academic example is employed to demonstrate the proposed approach.

Keywords: Conceptual solution, engineering design, hierarchical planning, multi-objective search, problem reduction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1007

Authors: Chiung-Hui Chen

Abstract:

The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: Behavior, big data, hierarchical Hidden Markov Model, intelligent object.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 764

Authors: G. M. Mir, Moinuddin, N. A. Shah

Abstract:

In the age of global communications, heterogeneous networks are seen to be the best choice of strategy to ensure continuous and uninterruptible services. This will allow mobile terminal to stay in connection even they are migrating into different segment coverage through the handoff process. With the increase of teletraffic demands in mobile cellular system, hierarchical cellular systems have been adopted extensively for more efficient channel utilization and better QoS (Quality of Service). This paper presents a bidirectional call overflow scheme between two layers of microcells and macrocells, where handoffs are decided by the velocity of mobile making the call. To ensure that handoff calls are given higher priorities, it is assumed that guard channels are assigned in both macrocells and microcells. A hysteresis value introduced in mobile velocity is used to allow mobile roam in the same cell if its velocity changes back within the set threshold values. By doing this the number of handoffs is reduced thereby reducing the processing overhead and enhancing the quality of service to the end user.

Keywords: Hierarchical cellular systems, hysteresis, overflow, threshold.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1369

Authors: Mounira Taileb, Sid Lamrous, Sami Touati

Abstract:

In order to accelerate the similarity search in highdimensional database, we propose a new hierarchical indexing method. It is composed of offline and online phases. Our contribution concerns both phases. In the offline phase, after gathering the whole of the data in clusters and constructing a hierarchical index, the main originality of our contribution consists to develop a method to construct bounding forms of clusters to avoid overlapping. For the online phase, our idea improves considerably performances of similarity search. However, for this second phase, we have also developed an adapted search algorithm. Our method baptized NOHIS (Non-Overlapping Hierarchical Index Structure) use the Principal Direction Divisive Partitioning (PDDP) as algorithm of clustering. The principle of the PDDP is to divide data recursively into two sub-clusters; division is done by using the hyper-plane orthogonal to the principal direction derived from the covariance matrix and passing through the centroid of the cluster to divide. Data of each two sub-clusters obtained are including by a minimum bounding rectangle (MBR). The two MBRs are directed according to the principal direction. Consequently, the nonoverlapping between the two forms is assured. Experiments use databases containing image descriptors. Results show that the proposed method outperforms sequential scan and SRtree in processing k-nearest neighbors.

Keywords: K-nearest neighbour search, multi-dimensional indexing, multimedia databases, similarity search.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1561

Authors: Zhidong Zhang, Zhi-Chao Zhang

Abstract:

This study examined the mental health and behavioral problems in early adolescence with the instrument of Achenbach System of Empirically Based Assessment (ASEBA). The purpose of the study was stratified sampling method was used to collect data from 1975 participants. Multiple regression models and hierarchical regression models were applied to examine the relations between the background variables and internalizing problems, and the ones between students’ performance and internalizing problems. The results indicated that several background variables as predictors could significantly predict the anxious/depressed problem; reading and social study scores could significantly predict the anxious/depressed problem. However the class as a hierarchical macro factor did not indicate the significant effect. In brief, the majority of these models represented that the background variables, behaviors and academic performance were significantly related to the anxious/depressed problem.

Keywords: Behavioral problems, anxious/depression problems, empirical-based assessment, hierarchical modeling.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1759

Authors: Yasmin Mohd Yacob, Harsa A. Mat Sakim, Nor Ashidi Mat Isa

Abstract:

Feature selection study is gaining importance due to its contribution to save classification cost in terms of time and computation load. In search of essential features, one of the methods to search the features is via the decision tree. Decision tree act as an intermediate feature space inducer in order to choose essential features. In decision tree-based feature selection, some studies used decision tree as a feature ranker with a direct threshold measure, while others remain the decision tree but utilized pruning condition that act as a threshold mechanism to choose features. This paper proposed threshold measure using Manhattan Hierarchical Cluster distance to be utilized in feature ranking in order to choose relevant features as part of the feature selection process. The result is promising, and this method can be improved in the future by including test cases of a higher number of attributes.

Keywords: Feature ranking, decision tree, hierarchical cluster, Manhattan distance.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1968

Authors: Mohammad Taghi Taghavifard, Danial Mirheydari

Abstract:

This paper suggests an algorithm for the evaluation and selection of suppliers. At the beginning, all the needed materials and services used by the organization were identified and categorized with regard to their nature by ABC method. Afterwards, in order to reduce risk factors and maximize the organization's profit, purchase strategies were determined. Then, appropriate criteria were identified for primary evaluation of suppliers applying to the organization. The output of this stage was a list of suppliers qualified by the organization to participate in its tenders. Subsequently, considering a material in particular, appropriate criteria on the ordering of the mentioned material were determined, taking into account the particular materials' specifications as well as the organization's needs. Finally, for the purpose of validation and verification of the proposed model, it was applied to Mobarakeh Steel Company (MSC), the qualified suppliers of this Company are ranked by the means of a Hierarchical Fuzzy TOPSIS method. The obtained results show that the proposed algorithm is quite effective, efficient and easy to apply.

Keywords: ABC analysis, Hierarchical Fuzzy TOPSIS, Primary supplier evaluation, Purchasing strategy, supplier selection

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1403

Authors: Haidar Safa, Hassan Artail, Ahmad Mehio, Hicham Zahr, Ziad Matragi

Abstract:

The Mobile IP Standard has been developed to support mobility over the Internet. This standard contains several drawbacks as in the cases where packets are routed via sub-optimal paths and significant amount of signaling messages is generated due to the home registration procedure which keeps the network aware of the current location of the mobile nodes. Recently, a dynamic hierarchical mobility management strategy for mobile IP networks (DHMIP) has been proposed to reduce home registrations costs. However, this strategy induces a packet delivery delay and increases the risk of packet loss. In this paper, we propose an enhanced version of the dynamic hierarchical strategy that reduces the packet delivery delay and minimizes the risk of packet loss. Preliminary results obtained from simulations are promising. They show that the enhanced version outperforms the original dynamic hierarchical mobility management strategy version.

Keywords: Location management, Mobile IP (MIP), Home Agent, Foreign Agent.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1445

Authors: Seung-Jun Yu, Young-Min Ko, Hyoung-Kyu Song

Abstract:

Recently developed cooperative diversity scheme enables a terminal to get transmit diversity through the support of other terminals. However, most of the introduced cooperative schemes have a common fault of decreased transmission rate because the destination should receive the decodable compositions of symbols from the source and the relay. In order to achieve high data rate, we propose a cooperative scheme that employs hierarchical modulation. This scheme is free from the rate loss and allows seamless cooperative communication.

Keywords: Cooperative communication, hierarchical modulation, high data rate, transmission scheme.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1890

Authors: Achmad Nizar Hidayanto, Elisabeth Martha Koeanan

Abstract:

Image clustering is a process of grouping images based on their similarity. The image clustering usually uses the color component, texture, edge, shape, or mixture of two components, etc. This research aims to explore image clustering using color composition. In order to complete this image clustering, three main components should be considered, which are color space, image representation (feature extraction), and clustering method itself. We aim to explore which composition of these factors will produce the best clustering results by combining various techniques from the three components. The color spaces use RGB, HSV, and L*a*b* method. The image representations use Histogram and Gaussian Mixture Model (GMM), whereas the clustering methods use KMeans and Agglomerative Hierarchical Clustering algorithm. The results of the experiment show that GMM representation is better combined with RGB and L*a*b* color space, whereas Histogram is better combined with HSV. The experiments also show that K-Means is better than Agglomerative Hierarchical for images clustering.

Keywords: Image clustering, feature extraction, RGB, HSV, L*a*b*, Gaussian Mixture Model (GMM), histogram, Agglomerative Hierarchical Clustering (AHC), K-Means, Expectation-Maximization (EM).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2205

Authors: Hong Pan, Yaping Zhu, Liang Zheng Xia

Abstract:

We propose a fast and robust hierarchical face detection system which finds and localizes face images with a cascade of classifiers. Three modules contribute to the efficiency of our detector. First, heterogeneous feature descriptors are exploited to enrich feature types and feature numbers for face representation. Second, a PSO-Adaboost algorithm is proposed to efficiently select discriminative features from a large pool of available features and reinforce them into the final ensemble classifier. Compared with the standard exhaustive Adaboost for feature selection, the new PSOAdaboost algorithm reduces the training time up to 20 times. Finally, a three-stage hierarchical classifier framework is developed for rapid background removal. In particular, candidate face regions are detected more quickly by using a large size window in the first stage. Nonlinear SVM classifiers are used instead of decision stump functions in the last stage to remove those remaining complex nonface patterns that can not be rejected in the previous two stages. Experimental results show our detector achieves superior performance on the CMU+MIT frontal face dataset.

Keywords: Adaboost, Face detection, Feature selection, PSO

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2198

Authors: Kamal K.Bharadwaj, Rekha Kandwal

Abstract:

An important structuring mechanism for knowledge bases is building clusters based on the content of their knowledge objects. The objects are clustered based on the principle of maximizing the intraclass similarity and minimizing the interclass similarity. Clustering can also facilitate taxonomy formation, that is, the organization of observations into a hierarchy of classes that group similar events together. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. In this paper, a set of related HPRs is called a cluster and is represented by a HPR-tree. This paper discusses an algorithm based on cumulative learning scenario for dynamic structuring of clusters. The proposed scheme incrementally incorporates new knowledge into the set of clusters from the previous episodes and also maintains summary of clusters as Synopsis to be used in the future episodes. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested incremental structuring of clusters would be useful in mining data streams.

Keywords: Cumulative learning, clustering, data mining, hierarchical production rules.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1437

Authors: P. Puustinen, A. Kanto

Abstract:

This paper proposes a new procedure for analyzing means-end chain data in marketing research. Most commonly the collected data is summarized in the Hierarchical Value Map (HVM) illustrating the main attribute-consequence-value linkages. This paper argues that traditionally constructed HVM may give an erroneous impression of the results of a means-end study. To justify the arguments, an alternative procedure to (1) determine the dominant attribute-consequence-value linkages and (2) construct HVM in a precise manner is presented. The current approach makes a contribution to means-end analysis, allowing marketers to address a set of marketing problems, such as advertising strategy.

Keywords: Means-end chain analysis, Laddering, Hierarchical Value Map.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2790

Authors: Kavi K. Khedo, R. K. Subramanian

Abstract:

Wireless sensor networks (WSN) are currently receiving significant attention due to their unlimited potential. These networks are used for various applications, such as habitat monitoring, automation, agriculture, and security. The efficient nodeenergy utilization is one of important performance factors in wireless sensor networks because sensor nodes operate with limited battery power. In this paper, we proposed the MiSense hierarchical cluster based routing algorithm (MiCRA) to extend the lifetime of sensor networks and to maintain a balanced energy consumption of nodes. MiCRA is an extension of the HEED algorithm with two levels of cluster heads. The performance of the proposed protocol has been examined and evaluated through a simulation study. The simulation results clearly show that MiCRA has a better performance in terms of lifetime than HEED. Indeed, MiCRA our proposed protocol can effectively extend the network lifetime without other critical overheads and performance degradation. It has been noted that there is about 35% of energy saving for MiCRA during the clustering process and 65% energy savings during the routing process compared to the HEED algorithm.

Keywords: Clustering algorithm, energy consumption, hierarchical model, sensor networks.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1779

Authors: Alexander Denzler, Marcel Wehrle, Andreas Meier

Abstract:

A knowledge base stores facts and rules about the world that applications can use for the purpose of reasoning. By applying the concept of granular computing to a knowledge base, several advantages emerge. These can be harnessed by applications to improve their capabilities and performance. In this paper, the concept behind such a construct, called a granular knowledge cube, is defined, and its intended use as an instrument that manages to cope with different data types and detect knowledge domains is elaborated. Furthermore, the underlying architecture, consisting of the three layers of the storing, representing, and structuring of knowledge, is described. Finally, benefits as well as challenges of deploying it are listed alongside application types that could profit from having such an enhanced knowledge base.

Keywords: Granular computing, granular knowledge, hierarchical structuring, knowledge bases.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2377

Authors: Tesnim Charrad, Kaouther Nouira, Ahmed Ferchichi

Abstract:

In order to reduce the number of deaths due to heart problems, we propose the use of Hierarchical Temporal Memory Algorithm (HTM) which is a real time anomaly detection algorithm. HTM is a cortical learning algorithm based on neocortex used for anomaly detection. In other words, it is based on a conceptual theory of how the human brain can work. It is powerful in predicting unusual patterns, anomaly detection and classification. In this paper, HTM have been implemented and tested on ECG datasets in order to detect cardiac anomalies. Experiments showed good performance in terms of specificity, sensitivity and execution time.

Keywords: HTM, Real time anomaly detection, ECG, Cardiac Anomalies.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 794

Authors: Daniel I. Morariu, Radu G. Cretulescu, Lucian N. Vintan

Abstract:

In text categorization problem the most used method for documents representation is based on words frequency vectors called VSM (Vector Space Model). This representation is based only on words from documents and in this case loses any “word context" information found in the document. In this article we make a comparison between the classical method of document representation and a method called Suffix Tree Document Model (STDM) that is based on representing documents in the Suffix Tree format. For the STDM model we proposed a new approach for documents representation and a new formula for computing the similarity between two documents. Thus we propose to build the suffix tree only for any two documents at a time. This approach is faster, it has lower memory consumption and use entire document representation without using methods for disposing nodes. Also for this method is proposed a formula for computing the similarity between documents, which improves substantially the clustering quality. This representation method was validated using HAC - Hierarchical Agglomerative Clustering. In this context we experiment also the stemming influence in the document preprocessing step and highlight the difference between similarity or dissimilarity measures to find “closer" documents.

Keywords: Text Clustering, Suffix tree documentrepresentation, Hierarchical Agglomerative Clustering

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1909

Authors: L. K. Davis

Abstract:

The effects of the evolution force are observable in nature at all structural levels ranging from small molecular systems to conversely enormous biospheric systems. However, the evolution force and work associated with formation of biological structures has yet to be described mathematically or theoretically. In addressing the conundrum, we consider evolution from a unique perspective and in doing so we introduce the “Fundamental Theory of the Evolution Force: FTEF”. We utilized synthetic evolution artificial intelligence (SYN-AI) to identify genomic building blocks and to engineer 14-3-3 ζ docking proteins by transforming gene sequences into time-based DNA codes derived from protein hierarchical structural levels. The aforementioned served as templates for random DNA hybridizations and genetic assembly. The application of hierarchical DNA codes allowed us to fast forward evolution, while dampening the effect of point mutations. Natural selection was performed at each hierarchical structural level and mutations screened using Blosum 80 mutation frequency-based algorithms. Notably, SYN-AI engineered a set of three architecturally conserved docking proteins that retained motion and vibrational dynamics of native Bos taurus 14-3-3 ζ.

Keywords: 14-3-3 docking genes, synthetic protein design, time based DNA codes, writing DNA code from scratch.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 664

Authors: Norashikin Ahmad, Damminda Alahakoon

Abstract:

Self-organizing map (SOM) provides both clustering and visualization capabilities in mining data. Dynamic self-organizing maps such as Growing Self-organizing Map (GSOM) has been developed to overcome the problem of fixed structure in SOM to enable better representation of the discovered patterns. However, in mining large datasets or historical data the hierarchical structure of the data is also useful to view the cluster formation at different levels of abstraction. In this paper, we present a technique to generate concept trees from the GSOM. The formation of tree from different spread factor values of GSOM is also investigated and the quality of the trees analyzed. The results show that concept trees can be generated from GSOM, thus, eliminating the need for re-clustering of the data from scratch to obtain a hierarchical view of the data under study.

Keywords: dynamic self-organizing map, concept formation, clustering.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1458

Authors: Hsin-Chang Yang, Chung-Hong Lee, Kuo-Lung Ke

Abstract:

The self-organizing map (SOM) model is a well-known neural network model with wide spread of applications. The main characteristics of SOM are two-fold, namely dimension reduction and topology preservation. Using SOM, a high-dimensional data space will be mapped to some low-dimensional space. Meanwhile, the topological relations among data will be preserved. With such characteristics, the SOM was usually applied on data clustering and visualization tasks. However, the SOM has main disadvantage of the need to know the number and structure of neurons prior to training, which are difficult to be determined. Several schemes have been proposed to tackle such deficiency. Examples are growing/expandable SOM, hierarchical SOM, and growing hierarchical SOM. These schemes could dynamically expand the map, even generate hierarchical maps, during training. Encouraging results were reported. Basically, these schemes adapt the size and structure of the map according to the distribution of training data. That is, they are data-driven or dataoriented SOM schemes. In this work, a topic-oriented SOM scheme which is suitable for document clustering and organization will be developed. The proposed SOM will automatically adapt the number as well as the structure of the map according to identified topics. Unlike other data-oriented SOMs, our approach expands the map and generates the hierarchies both according to the topics and their characteristics of the neurons. The preliminary experiments give promising result and demonstrate the plausibility of the method.

Keywords: Self-organizing map, topic identification, learning algorithm, text clustering.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2024

Authors: Erika Pigliapoco, Valerio Freschi, Alessandro Bogliolo

Abstract:

This work presents a new phonetic transcription system based on a tree of hierarchical pronunciation rules expressed as context-specific grapheme-phoneme correspondences. The tree is automatically inferred from a phonetic dictionary by incrementally analyzing deeper context levels, eventually representing a minimum set of exhaustive rules that pronounce without errors all the words in the training dictionary and that can be applied to out-of-vocabulary words. The proposed approach improves upon existing rule-tree-based techniques in that it makes use of graphemes, rather than letters, as elementary orthographic units. A new linear algorithm for the segmentation of a word in graphemes is introduced to enable outof- vocabulary grapheme-based phonetic transcription. Exhaustive rule trees provide a canonical representation of the pronunciation rules of a language that can be used not only to pronounce out-of-vocabulary words, but also to analyze and compare the pronunciation rules inferred from different dictionaries. The proposed approach has been implemented in C and tested on Oxford British English and Basic English. Experimental results show that grapheme-based rule trees represent phonetically sound rules and provide better performance than letter-based rule trees.

Keywords: Automatic phonetic transcription, pronunciation rules, hierarchical tree inference.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1924

Authors: Kristoffer Clyde Magsino, H. Srikanth Kamath

Abstract:

Wireless Sensor Network is widely used in electronics. Wireless sensor networks are now used in many applications including military, environmental, healthcare applications, home automation and traffic control. We will study one area of wireless sensor networks, which is the routing protocol. Routing protocols are needed to send data between sensor nodes and the base station. In this paper, we will discuss two routing protocols, such as datacentric and hierarchical routing protocol. We will show the output of the protocols using the NS-2 simulator. This paper will compare the simulation output of the two routing protocol using Nam. We will simulate using Xgraph to find the throughput and delay of the protocol.

Keywords: data-centric routing protocol, hierarchical routingprotocol, Nam, NS-2, Routing Protocol, sensor nodes, SPIN, throughput, Xgraph

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2119

Authors: Suraiya Jabin, Kamal K. Bharadwaj

Abstract:

This research presents a system for post processing of data that takes mined flat rules as input and discovers crisp as well as fuzzy hierarchical structures using Learning Classifier System approach. Learning Classifier System (LCS) is basically a machine learning technique that combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. Crisp description for a concept usually cannot represent human knowledge completely and practically. In the proposed Learning Classifier System initial population is constructed as a random collection of HPR–trees (related production rules) and crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is suggested for the proposed system and based on Subsumption Matrix (SM), a suitable fitness function is proposed. Suitable genetic operators are proposed for the chosen chromosome representation method. For implementing reinforcement a suitable reward and punishment scheme is also proposed. Experimental results are presented to demonstrate the performance of the proposed system.

Keywords: Hierarchical Production Rule, Data Mining, Learning Classifier System, Fuzzy Subsumption Relation, Subsumption matrix, Reinforcement Learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1455

Authors: Li Zhu, Binghua Wang, Yong Sun

Abstract:

China is experiencing the rural development process, with the agritourism complex becoming one of the significant modes. Therefore, it is imperative to understand the energy performance of agritourism complex. This study focuses on a typical case of the agritourism complex and simulates the energy consumption performance on condition of the regular energy system. It was found that HVAC took 90% of the whole energy demand range. In order to optimize the energy supply structure, the hierarchical analysis was carried out on the level of architecture with three main factors such as construction situation, building types and energy demand types. Finally, the energy planning suggestion of the agritourism complex was put forward and the relevant results were obtained.

Keywords: Agritourism complex, energy planning, energy demand simulation, hierarchical structure model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 895