scholarly journals Rule Based Replacement of Pronoun by Corresponding Noun for Bangla News Documents

2017 ◽  
Vol 8 (2) ◽  
pp. 26-42 ◽  
Author(s):  
Md. Majharul Haque ◽  
Suraiya Pervin ◽  
Zerina Begum
Keyword(s):  
Information Retrieval ◽  
Research Work ◽  
Dependency Parsing ◽  
Rule Based

The object of this research work is to replace pronoun by corresponding noun for Bangla news documents. To the best of our knowledge, this is the first initiative to solve the problem of dangling pronoun where corresponding noun is not available. If the information retrieval procedures extract any sentence with dangling pronoun, it may raise confusion to the user. To mitigate this problem, a method has been proposed here by using general and special tagging, dependency parsing, full name identifying and finally pronoun replacing. For achieving the target of this method, 3000 Bangla news documents have been analyzed and some grammar books have been studied. Seven knowledgeable persons in the arena of Bangla language also helped us in this research work. Finally, the proposed method shows 71.80% accuracy in the evaluation for replacing pronoun.

scholarly journals CONTEXT STORAGE USING CLOUD-BASED MONGODB WITH RULE-BASED RETE ALGORITHM

2021 ◽  
Vol 9 (2) ◽  
pp. 1022-1030
Author(s):  
Shivakumar. C, Et. al.
Keyword(s):  
Sensor Network ◽  
Context Awareness ◽  
Research Work ◽  
Context Aware ◽  
The Novel ◽  
Rule Based ◽  
Smart System ◽  
Context Aware Computing ◽  
Context Data ◽  
Day By Day

In this Context-aware computing era, everything is being automated and because of this, smart system’s count been incrementing day by day.  The smart system is all about context awareness, which is a synergy with the objects in the system. The result of the interaction between the users and the sensors is nothing but the repository of the vast amount of context data. Now the challenging task is to represent, store, and retrieve context data. So, in this research work, we have provided solutions to context storage. Since the data generated from the sensor network is dynamic, we have represented data using Context dimension tree, stored the data in cloud-based ‘MongoDB’, which is a NoSQL. It provides dynamic schema and reasoning data using If-Then rules with RETE algorithm. The Novel research work is the integration of NoSQL cloud-based MongoDB, rule-based RETE algorithm and CLIPS tool architecture. This integration helps us to represent, store, retrieve and derive inferences from the context data efficiently..                       

scholarly journals An Art of Review on Conceptual based Information Retrieval

Webology ◽  
2021 ◽  
Vol 18 (SI02) ◽  
pp. 21-31
Author(s):  
P. Mahalakshmi ◽  
N. Sabiyath Fathima
Keyword(s):  
Information Retrieval ◽  
Keyword Search ◽  
Semantic Representation ◽  
Research Work ◽  
Semantic Search ◽  
Future Research ◽  
Conceptual Information ◽  
Retrieval Systems ◽  
User Query ◽  
Information Retrieval Systems

Basically keywords are used to index and retrieve the documents for the user query in a conventional information retrieval systems. When more than one keywords are used for defining the single concept in the documents and in the queries, inaccurate and incomplete results were produced by keyword based retrieval systems. Additionally, manual interventions are required for determining the relationship between the related keywords in terms of semantics to produce the accurate results which have paved the way for semantic search. Various research work has been carried out on concept based information retrieval to tackle the difficulties that are caused by the conventional keyword search and the semantic search systems. This paper aims at elucidating various representation of text that is responsible for retrieving relevant search results, approaches along with the evaluation that are carried out in conceptual information retrieval, the challenges faced by the existing research to expatiate requirements of future research. In addition, the conceptual information that are extracted from the different sources for utilizing the semantic representation by the existing systems have been discussed.

scholarly journals A Novel Rule based Data Mining Approach towards Movie Recommender System

2020 ◽  
Vol 44 (1) ◽  
pp. 157-170
Author(s):  
Mugdha Sharma ◽  
Laxmi Ahuja ◽  
Vinay Kumar
Keyword(s):  
Recommender System ◽  
Recommendation System ◽  
Phase 1 ◽  
Research Work ◽  
Rule Learning ◽  
Rule Base ◽  
Individual Member ◽  
Phase 2 ◽  
Group Recommendation ◽  
Rule Based

The proposed research work is an effort to provide accurate movie recommendations to a group of users with the help of a rule-based content-based group recommender system. The whole approach is categorized into 2 phases. In phase 1, a rule- based approach has been proposed which considers the users’ viewing history to provide the Rule Base for every individual user. In phase 2, a novel group recommendation system has been proposed which considers the ratings of the movies as per the rule base generated in phase 1. Phase 2 also considers the weightage of every individual member of the group to provide the accurate movie recommendation to that particular group of users. The results of experimental setup also establish the fact that the proposed system provides more accurate outcomes in terms of precision and recall over other rule learning algorithms such as C4.5.

scholarly journals Deep Learning Based Question Answering Search Engine

2021 ◽  
pp. 25-32
Author(s):  
Mrunal Malekar
Keyword(s):  
Information Retrieval ◽  
Deep Learning ◽  
Natural Language ◽  
Search Engine ◽  
Language Processing ◽  
Question Answering ◽  
Research Work ◽  
Construction Company ◽  
Exact Answer ◽  
Search For Information

Domain based Question Answering is concerned with building systems which provide answers to natural language questions that are asked specific to a domain. It comes under Information Retrieval and Natural language processing. Using Information Retrieval, one can search for the relevant documents which may contain the answer but it won’t give the exact answer for the question asked. In the presented work, a question answering search engine has been developed which first finds out the relevant documents from a huge textual document data of a construction company and then goes a step beyond to extract answer from the extracted document. The robust question answering system developed uses Elastic Search for Information Retrieval [paragraphs extraction] and Deep Learning for answering the question from the short extracted paragraph. It leverages BERT Deep Learning Model to understand the layers and representations between the question and answer. The research work also focuses on how to improve the search accuracy of the Information Retrieval based Elastic Search engine which returns the relevant documents which may contain the answer.

scholarly journals Influence of GUJarati STEmmeR in Supervised Learning of Web Page Categorization

2021 ◽  
Vol 13 (3) ◽  
pp. 23-34
Author(s):  
Chandrakant D. Patel ◽  
◽  
Jayesh M. Patel
Keyword(s):  
Machine Learning ◽  
Information Retrieval ◽  
Research Work ◽  
Research Problem ◽  
Machine Learning Algorithms ◽  
Supervised Machine Learning ◽  
Web Page ◽  
User Query ◽  
On Line ◽  
Gujarati Language

With the large quantity of information offered on-line, it's equally essential to retrieve correct information for a user query. A large amount of data is available in digital form in multiple languages. The various approaches want to increase the effectiveness of on-line information retrieval but the standard approach tries to retrieve information for a user query is to go looking at the documents within the corpus as a word by word for the given query. This approach is incredibly time intensive and it's going to miss several connected documents that are equally important. So, to avoid these issues, stemming has been extensively utilized in numerous Information Retrieval Systems (IRS) to extend the retrieval accuracy of all languages. These papers go through the problem of stemming with Web Page Categorization on Gujarati language which basically derived the stem words using GUJSTER algorithms [1]. The GUJSTER algorithm is based on morphological rules which is used to derived root or stem word from inflected words of the same class. In particular, we consider the influence of extracted a stem or root word, to check the integrity of the web page classification using supervised machine learning algorithms. This research work is intended to focus on the analysis of Web Page Categorization (WPC) of Gujarati language and concentrate on a research problem to do verify the influence of a stemming algorithm in a WPC application for the Gujarati language with improved accuracy between from 63% to 98% through Machine Learning supervised models with standard ratio 80% as training and 20% as testing.

scholarly journals A Novel Information retrieval system for distributed cloud using Hybrid Deep Fuzzy Hashing Algorithm

2020 ◽  
Vol 02 (03) ◽  
pp. 151-160 ◽  
Author(s):  
Dr. V. Suma
Keyword(s):  
Neural Network ◽  
Information Retrieval ◽  
Deep Neural Network ◽  
Research Work ◽  
Support Vector ◽  
Retrieval Performance ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Hashing Algorithm ◽  
Distributed Cloud

The recent technology development fascinates the people towards information and its services. Managing the personal and pubic data is a perennial research topic among researchers. In particular retrieval of information gains more attention as it is important similar to data storing. Clustering based, similarity based, graph based information retrieval systems are evolved to reduce the issues in conventional information retrieval systems. Learning based information retrieval is the present trend and in particular deep neural network is widely adopted due to its retrieval performance. However, the similarity between the information has uncertainties due to its measuring procedures. Considering these issues also to improve the retrieval performance, a hybrid deep fuzzy hashing algorithm is introduced in this research work. Hashing efficiently retrieves the information based on mapping the similar information as correlated binary codes and this underlying information is trained using deep neural network and fuzzy logic to retrieve the necessary information from distributed cloud. Experimental results prove that the proposed model attains better retrieval accuracy and accuracy compared to conventional models such as support vector machine and deep neural network.

scholarly journals Abstract Rule Based Pattern Learning with Neural Networks

2020 ◽  
Vol 34 (10) ◽  
pp. 13718-13719
Author(s):  
Radha Manisha Kopparti
Keyword(s):  
Neural Networks ◽  
Research Work ◽  
Pattern Learning ◽  
Rule Based ◽  
Abstract Rule

In this research work, the problem of learning abstract rules using neural networks is studied and a solution called ‘Relation Based Patterns’ (RBP) which model abstract relationships based on equality is proposed.

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