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A Natural Language Based Retrieval System for Data Warehouse Using Multi-Dimensional Entity Relationship Model

Thesis Info

Access Option

External Link

Author

Majeed, Fiaz

Program

PhD

Institute

University of Engineering and Technology

City

Lahore

Province

Punjab

Country

Pakistan

Thesis Completing Year

2016

Thesis Completion Status

Completed

Subject

Computer Science

Language

English

Link

http://prr.hec.gov.pk/jspui/bitstream/123456789/11363/1/Fiaz%20Majeed_CS_2016_UET%28L%29_PRR.pdf

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676727686473

Similar


Natural Language Interfaces to Databases (NLIDB) is an area of research that deals with the representation of users request to database in their native language. Currently, data warehouses are widely used by enterprises for decision making. It is important to mention that characteristics of decision-making systems are inherently different from transactional systems. The users of decision-making systems are top management (executives) who are normally non-technical having less knowledge of the data warehouse schema and about writing database technical queries. In fact, ad-hoc query is the information need of user that may not be fulfilled with front-end tools having predefined capabilities e.g. Reporting, OLAP or Data mining tools etc. Such information needs are not easy to express in technical query language. This motivated us to propose a Natural Language Based Retrieval System for Data Warehouse (NLRSDW) to support users especially in the ad-hoc query development.A Logical Schema-based Mapping (LSM) technique has been developed. Using this technique, targeted search is performed efficiently in the data instances. For targeted search, a LSM oriented mechanism has been presented. In addition, 3 searching strategies are elaborated which include 1) Identified elements searching 2) Proximal elements searching and 3) Level-wise searching to retrieve the matching instances for each data value. The retrieved instances are ranked with 5 criterions based on which an algorithm has been developed. Furthermore, solution to identify the aggregation constructs (i.e. aggregation function, measure, level and grouping attributes) accurately has been presented. Data Warehouses maintain aggregated computations to efficiently answer queries on large volume of data. It is very challenging task to interpret accurate aggregation constructs from the keyword-based query written on the Natural Language Interface to Data Warehouse. Later, a semi-automatic approach to build the Data Warehouse logical Schema-based Domain Thesaurus is proposed.This approach takes the Data Warehouse logical Schema as input and generates Domain Thesaurus using multiple sources containing Schema, Data Instances, WordNet, WWW and Domain Repository. The Thesaurus evolution approach is also presented which shows how Thesaurus can be technically expanded at user query time.An in-depth experimental evaluation has been carried out in comparison to existing systems. The results are encouraging. Using NLRSDW, non-technical users can easily write any ad-hoc information need in natural language. As a result, executives do not have to take support of IT staff and time to develop query is negligible.
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دنیا دی حقیقت

دنیا دی حقیقت
حسن جوانی دا اے روپ نہیوں رہنا
ہک دن آسی، توں ہے دکھاں وچ پینا

کرسی وفا تیرے نال نہ جوانی
ٹر جاوے ہک واری پھر ناں ایہہ آنی
ایہہ تیری مغروری ساری ٹٹ جانی
پانی والی لہر وانگوں زندگی نے وہنا
حسن جوانی دا اے روپ نہیوں رہنا

ماں تیری ہر گل کردی ہے پوری
ہتھاں نال ٹورے تینوں اوہدی مجبوری
ہک دن چھڈنا جہان اے ضروری
نیکیاں دا پا لَے توں گل وچ گہنا
حسن جوانی دا اے روپ نہیوں رہنا

نخرے نیں چار دن فیر پچھتانا
حسن گیا تے گیا سب یارانا
عشق حقیقی نے ای ساتھ نبھانا
قادریؔ سائیں دا توں من لَے کہنا
حسن جوانی دا اے روپ نہیوں رہنا

چڑھدی جوانی بڑا شور ہے مچایا
چوڑیاں تے جھانجھراں نے دل بہلایا
حسن دے پچاریاں نوں بڑا توں ستایا
روپ والے بت تیرے ہک دن ڈھہنا
حسن جوانی دا اے روپ نہیوں رہنا

قادریؔ ایہہ محفلاں نہ ایہہ ویلے آنے
نویں ایتھے آ گئے ، پرانے ٹر جانے
اگے والی سوچ، گل کہندے نیں سیانے
سدا نہیوں جوبنے تے ایہہ رنگ رہنا
حسن جوانی دا اے روپ نہیوں رہنا

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Extremism is a challenge facing the societies both on secular and religious level, which has damaged the society with disrupting peace and creating caos in the world. There is a dire need of an academic discussion regarding the various aspects of the issue in Islamic and social perspectives. This is an attempt to realize the sensitivity of the subject and providing a balanced approached in the light of Islamic teachings. This article draws attention of the concerned authorities to play their role for the stoppage of blasphemous activities by implementation of the existing law and its development by determining the punishment against false accusation. The article also explains that what Islam expects from the Muslims and guides them in expressing their feelings and showing their attitudes, behavior and fixing their responsibilities regarding the issue with true Islamic spirit. The article draws the attention of the non-Muslim countries and communities as well to display impartiality, truth and realistic attitude and appropriate legislation by considering the blasphemous activities as a heinous crime.

Impact of Overconfidence and Loss Aversion Biases on Equity investors Decision Making Process and Performance

The purpose of this study was to investigating the behavioral factors that having an impact of individual equity investors' investment decision making process together with investment performance at Pakistan's Stock Markets. Moreover, the relationship of these behavioral variables with investment decision making process and performance are also monitored. As in Pakistan, there are limited work is done in the area of behavioral finance, this study is considered to add significantly to the advancement of this field in Pakistan. The study starts with the previous theories in behavioral finance. So, on the basis of those theories researcher develop hypotheses. After that, these hypotheses are tested in the course of the questionnaires which are distributed to individual equity investor's at Pakistan's Stock Exchanges. Then the collected data are analyzed by using Statistical software. The Tests used were, Exploratory Factor Analysis (EFA), Descriptive Statistics (DS), Cronbach's Alpha, Pearson Correlation Coefficient and also Multiple Linear Regression (MLR) alongwith Soble Test. The result shows that these are two mainly behavioral factors: Heuristic Theory (Overconfidence Bias) and Prospect Theory (Loss Aversion Bias), affecting the investment decisions making process and performance of individual equity investors. Most of the sub-variables of both behavioral biases contain high impact on the performance of equity investor. And these behavioral biases along with or without mediating variable (partial mediation exist through Sobel test) also contain positive impact on investment performance of individual equity investor at Pakistan's Stock Markets. The findings of this study is not only helpful to the individual equity investors, authors, security companies, but also for the field of behavioral finance. Because, here the only two behavioral biases (Overconfidence and Loss aversion) impact is deeply observed and draw the conclusions.