scholarly journals A Mind Map Query in Information Retrieval : The 'User Query Idea' Concept and Preliminary Results

2014 ◽  
Author(s):  
Rihab Ayed ◽  
Farah Harrathi ◽  
Mohsen Gammoudi M ◽  
Mahran Farhat
Keyword(s):  
Information Retrieval ◽  
Preliminary Results ◽  
User Query

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

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.

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

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.

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.

Uncertain Confidence Network-Based Collaborative Information Retrieval Relevance Feedback Algorithm

2020 ◽  
pp. 20-39
Author(s):  
Fatiha Naouar ◽  
Lobna Hlaoua ◽  
Mohamed Nazih Omri
Keyword(s):  
Information Retrieval ◽  
Relevance Feedback ◽  
Information Source ◽  
Strong Association ◽  
Relevant Information ◽  
User Query ◽  
Proposed Model ◽  
Evidence Source ◽  
Feedback Algorithm ◽  
Collaborative Information Retrieval

Collaborative retrieval allows increasing the amount of relevant information found and sharing history with others. The collaborative retrieval can reduce the retrieval time performed by the users of the same profile. This chapter proposes a new relevance feedback algorithm to collaborative information retrieval based on a confidence network, which performs propagation relevance between annotations terms. The main contribution in this work is the extraction of relevant terms to reformulate the initial user query considering the annotations as an information source. The proposed model introduces the concept of necessity that allows determining the terms that have strong association relationships estimated to the measure of a confidence. Since the user is overwhelmed by a variety of contradictory annotations, another contribution consists of determining the relevant annotations for a given evidence source. The experimental study gives very encouraging results.

PERSONALIZING THE SOURCE SELECTION AND THE RESULT MERGING PROCESS

2009 ◽  
Vol 18 (02) ◽  
pp. 331-354 ◽  
Author(s):  
SAMIR KECHID ◽  
HABIBA DRIAS
Keyword(s):  
Information Retrieval ◽  
Information Needs ◽  
Retrieval System ◽  
Information Source ◽  
Information Access ◽  
Information Retrieval System ◽  
Specific Information ◽  
Distributed Environment ◽  
Source Selection ◽  
User Query

The World Wide Web knows an incessant and very fast development. Currently, finding useful information on the Web is a time consuming process. In this paper, we present PIRS a personalized Information Retrieval System in a distributed environment. Most prior research in distributed information access focused on selecting and merging information that has the most relevant content according to the query but ignored the user's specific needs. The underlying idea is that different users have different backgrounds, goals and interests when seeking information and thus, the same query may cover different specific information needs according to who emitted it. However, with the ever expanding Web, users are faced with a huge number of information resources. Consequently, such query-based information access strategies lead to inaccurate query results. PIRS extends the state of the art in a Web-based information retrieval system in distributed environment. First, it develops models for representing both user and information source using feature based profiles. Second, PIRS expands a user query according to his profile. Third, it develops algorithms for source selection and results merging that personalize the computation of the relevance score of a document in response to the user's query. PIRS has been experimented with several known information source. The experimental results obtained show the effectiveness of our approach.

scholarly journals Text Mining in Cybersecurity: Exploring Threats and Opportunities

2019 ◽  
Vol 3 (3) ◽  
pp. 62 ◽  
Author(s):  
Maaike H. T. de Boer ◽  
Babette J. Bakker ◽  
Erik Boertjes ◽  
Mike Wilmer ◽  
Stephan Raaijmakers ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Text Mining ◽  
State Of The Art ◽  
Data Sources ◽  
Added Value ◽  
Design Decision ◽  
User Evaluation ◽  
User Query ◽  
Overall Evaluation ◽  
Speed Up

The number of cyberattacks on organizations is growing. To increase cyber resilience, organizations need to obtain foresight to anticipate cybersecurity vulnerabilities, developments, and potential threats. This paper describes a tool that combines state of the art text mining and information retrieval techniques to explore the opportunities of using these techniques in the cybersecurity domain. Our tool, the Horizon Scanner, can scrape and store data from websites, blogs and PDF articles, and search a database based on a user query, show textual entities in a graph, and provide and visualize potential trends. The aim of the Horizon Scanner is to help experts explore relevant data sources for potential threats and trends and to speed up the process of foresight. In a requirements session and user evaluation of the tool with cyber experts from the Dutch Defense Cyber Command, we explored whether the Horizon Scanner tool has the potential to fulfill its aim in the cybersecurity domain. Although the overall evaluation of the tool was not as good as expected, some aspects of the tool were found to have added value, providing us with valuable insights into how to design decision support for forecasting analysts.

scholarly journals Ontology Knowledge based Information Retrieval for User Query Interpretation

2014 ◽  
Vol 12 (6) ◽  
pp. 245-252
Author(s):  
Nanju Kim ◽  
Hyejin Pyo ◽  
Hoon Jeong ◽  
Euiin Choi
Keyword(s):  
Information Retrieval ◽  
Knowledge Based ◽  
User Query ◽  
Query Interpretation

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 Onto Semantic Tourism Information Retrieval

2018 ◽  
Vol 7 (4.7) ◽  
pp. 148 ◽  
Author(s):  
Shilpa S. Laddha ◽  
Dr. Pradip M. Jawandhiya
Keyword(s):  
Information Retrieval ◽  
Significant Role ◽  
Semantic Search ◽  
Efficient Search ◽  
Domain Specific ◽  
Search Results ◽  
User Query ◽  
Tourism Information ◽  
Relationship Of ◽  
The Relationship

Semantic Search is an area of research which focuses on meaning of terms used in user query. Ontology plays significant role to define the concept and the relationship of terms in domain. Since the understanding of concepts is domain specific, Ontology creation is also domain specific. According to this argument, query interpreted in Tourism domain can have different meaning in some other domain. This paper presents a prototype of information retrieval interface using ontology which can save users time by rendering relevant, precise and efficient search results as compared to traditional search interfaces.  

OBIRE

2010 ◽  
Vol 1 (4) ◽  
pp. 58-73
Author(s):  
Xiangyu Liu ◽  
Maozhen Li ◽  
Yang Liu ◽  
Man Qi
Keyword(s):  
Fuzzy Logic ◽  
Information Retrieval ◽  
Domain Knowledge ◽  
P2p Network ◽  
The Internet ◽  
Bibliographic Record ◽  
P2p Networks ◽  
Bibliographic Information ◽  
User Query ◽  
Bibliographic Records

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.

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