OBIRE

It has been widely recognized that bibliographic information plays an increasingly important role for scientific research. Peer-to-peer (P2P) networks provide an effective environment for people belonging to a community to share various resources on the Internet. This paper presents OBIRE, an ontology based P2P network for bibliographic information retrieval. For a user query, OBIRE computes the degree of matches to indicate the similarity of a published record to the query. When searching for information, users can incorporate their domain knowledge into their queries which guides OBIRE to discover the bibliographic records that are of most interest of users. In addition, fuzzy logic based user recommendations are used to compute the trustiness of a set of keywords used by a bibliographic record which assists users in selecting bibliographic records. OBIRE is evaluated from the aspects of precision and recall, and experimental results show the effectiveness of OBIRE in bibliographic information retrieval.

Download Full-text

Designing a Chat-Bot for College Information using Information Retrieval and Automatic Text Summarization Techniques

Current Chinese Computer Science ◽

10.2174/2665997201999201022191540 ◽

2020 ◽

Vol 01 ◽

Author(s):

Radha Guha

Keyword(s):

Information Retrieval ◽

Language Processing ◽

Latent Dirichlet Allocation ◽

Semantic Analysis ◽

Text Summarization ◽

The Internet ◽

Specific Domain ◽

User Query ◽

College Information ◽

Chat Bot

Background:: In the era of information overload it is very difficult for a human reader to make sense of the vast information available in the internet quickly. Even for a specific domain like college or university website it may be difficult for a user to browse through all the links to get the relevant answers quickly. Objective:: In this scenario, design of a chat-bot which can answer questions related to college information and compare between colleges will be very useful and novel. Methods:: In this paper a novel conversational interface chat-bot application with information retrieval and text summariza-tion skill is designed and implemented. Firstly this chat-bot has a simple dialog skill when it can understand the user query intent, it responds from the stored collection of answers. Secondly for unknown queries, this chat-bot can search the internet and then perform text summarization using advanced techniques of natural language processing (NLP) and text mining (TM). Results:: The advancement of NLP capability of information retrieval and text summarization using machine learning tech-niques of Latent Semantic Analysis(LSI), Latent Dirichlet Allocation (LDA), Word2Vec, Global Vector (GloVe) and Tex-tRank are reviewed and compared in this paper first before implementing them for the chat-bot design. This chat-bot im-proves user experience tremendously by getting answers to specific queries concisely which takes less time than to read the entire document. Students, parents and faculty can get the answers for variety of information like admission criteria, fees, course offerings, notice board, attendance, grades, placements, faculty profile, research papers and patents etc. more effi-ciently. Conclusion:: The purpose of this paper was to follow the advancement in NLP technologies and implement them in a novel application.

Download Full-text

Application of Ontology Technology in Agricultural Information Retrieval

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.756-759.1249 ◽

2013 ◽

Vol 756-759 ◽

pp. 1249-1253 ◽

Cited By ~ 1

Author(s):

Jin Cui Kang ◽

Jing Long Gao

Keyword(s):

Information Retrieval ◽

Knowledge Base ◽

Domain Knowledge ◽

The Internet ◽

Related Information ◽

Agricultural Knowledge ◽

Intelligent Searching ◽

Knowledge Ontology

The agricultural information on the internet become more and more, it is very difficult to search accurate related information from such different information, in order to improve the efficiency of information retrieval on the internet, the intelligent searching technology of agricultural information based on ontology is proposed. The paper firstly introduces research on the agricultural ontology and information retrieval, and takes agriculture domain knowledge as research object, analyzes the characters of agricultural domain knowledge and semantics retrieval, then uses the agricultural ontology to make the structure of agriculture ontology knowledge, and constructs the related agricultural knowledge ontology and knowledge base, implementing the intelligent searching of the agricultural information. The results indicate that the application of agricultural ontology technology in the agricultural information retrieval not only achieves the intelligent retrieval of agricultural information, but also greatly improves the accuracy and reliability of agricultural information retrieval.

Download Full-text

Hybrid Term-Similarity-Based Clustering Approach and Its Applications

Handbook of Research on Investigations in Artificial Life Research and Development - Advances in Computational Intelligence and Robotics ◽

10.4018/978-1-5225-5396-0.ch018 ◽

2018 ◽

pp. 397-423

Author(s):

Banage T. G. S. Kumara ◽

Incheon Paik ◽

Koswatte R. C. Koswatte

Keyword(s):

Information Retrieval ◽

Empirical Study ◽

Service Discovery ◽

Experimental Results ◽

The Internet ◽

High Quality ◽

Internet Service ◽

Efficient Approach ◽

Term Similarity ◽

Clustering Approach

With the large number of web services now available via the internet, service discovery, recommendation, and selection have become a challenging and time-consuming task. Organizing services into similar clusters is a very efficient approach. A principal issue for clustering is computing the semantic similarity. Current approaches use methods such as keyword, information retrieval, or ontology-based methods. These approaches have problems that include discovering semantic characteristics, loss of semantic information, and a shortage of high-quality ontologies. Thus, the authors present a method that first adopts ontology learning to generate ontologies via the hidden semantic patterns existing within complex terms. Then, they propose service recommendation and selection approaches based on proposed clustering approach. Experimental results show that the term-similarity approach outperforms comparable existing clustering approaches. Further, empirical study of the prototyping recommendation and selection approaches have proved the effectiveness of proposed approaches.

Download Full-text

Design and Simulation of Smart Control System for Internet Traffic Distribution on Servers by Using Fuzzy Logic System

Al-Kitab Journal for Pure Sciences ◽

10.32441/kjps.v2i1.138 ◽

2018 ◽

Vol 2 (1) ◽

Author(s):

Raid Daoud ◽

Yaareb Al-Khashab

Keyword(s):

Fuzzy Logic ◽

Control System ◽

Input Parameter ◽

Traffic Density ◽

The Internet ◽

Linguistic Variables ◽

Internet Service ◽

Traffic Distribution ◽

Smart Control ◽

High Level

The internet service is provided by a given number of servers located in the main node of internet service provider (ISP). In some cases; the overload problem was occurred because a demand on a given website goes to very high level. In this paper, a fuzzy logic control (FLC) has proposed to distribute the load into the internet servers by a smart and flexible manner. Three effected parameters are tacked into account as input for FLC: link capacity which has three linguistic variables with Gaussian membership function (MF): (small, medium and big), traffic density with linguistic variables (low, normal and high) and channel latency with linguistic variables (empty, half and full); with one output which is the share server status (single, simple and share). The proposed work has been simulated by using MATLAB 2016a, by building a structure in the Fuzzy toolbox. The results were fixed by two manners: the graphical curves and the numerical tables, the surface response was smoothly changed and translates the well-fixed control system. The numerical results of the control system satisfy the idea of the smart rout for the incoming traffics from the users to internet servers. So, the response of the proposed system for the share of server ratio is 0.122, when the input parameter in the smallest levels; and the ratio is 0.879 when the input parameters are in highest level. The smart work and flexible use for the FLC is the main success solution for most of today systems control.

Download Full-text

Detecting “DeepFakes” in H.264 Video Data Using Compression Ghost Artifacts

Electronic Imaging ◽

10.2352/issn.2470-1173.2020.4.mwsf-116 ◽

2020 ◽

Vol 2020 (4) ◽

pp. 116-1-116-7

Author(s):

Raphael Antonius Frick ◽

Sascha Zmudzinski ◽

Martin Steinebach

Keyword(s):

Image Forensics ◽

Video Data ◽

Experimental Results ◽

Video Sequences ◽

The Internet ◽

Video Content ◽

High Quality ◽

The Public

In recent years, the number of forged videos circulating on the Internet has immensely increased. Software and services to create such forgeries have become more and more accessible to the public. In this regard, the risk of malicious use of forged videos has risen. This work proposes an approach based on the Ghost effect knwon from image forensics for detecting forgeries in videos that can replace faces in video sequences or change the mimic of a face. The experimental results show that the proposed approach is able to identify forgery in high-quality encoded video content.

Download Full-text

Semantic Representation of a Geo-Social User Profile for a Personalised Information Retrieval

Journal of Information & Knowledge Management ◽

10.1142/s0219649221500441 ◽

2021 ◽

pp. 2150044

Author(s):

Tahar Rafa ◽

Samir Kechid

Keyword(s):

Information Retrieval ◽

Information Search ◽

Semantic Representation ◽

User Profile ◽

Search Process ◽

Search System ◽

User Interactions ◽

User Interests ◽

Situational Contexts ◽

User Query

The user-centred information retrieval needs to introduce semantics into the user modelling for a meaningful representation of user interests. The semantic representation of the user interests helps to improve the identification of the user’s future cognitive needs. In this paper, we present a semantic-based approach for a personalised information retrieval. This approach is based on the design and the exploitation of a user profile to represent the user and his interests. In this user profile, we combine an ontological semantics issued from WordNet ontology, and a personal semantics issued from the different user interactions with the search system and with his social and situational contexts of his previous searches. The personal semantics considers the co-occurrence relations between relevant components of the user profile as semantic links. The user profile is used to improve two important phases of the information search process: (i) expansion of the initial user query and (ii) adaptation of the search results to the user interests.

Download Full-text