Effects of Query Complexity and Learning on Novice User Query Performance With Conceptual and Logical Database Interfaces

2004 ◽  
Vol 34 (2) ◽  
pp. 276-281 ◽  
Author(s):  
K.L. Siau ◽  
H.C. Chan ◽  
K.K. Wei
Keyword(s):  
Query Complexity ◽  
Novice User ◽  
Query Performance ◽  
User Query

The Effects on End-User Query Performance of Incorporating Object-Oriented Abstractions in Database Accounting Systems

2005 ◽  
Vol 19 (1) ◽  
pp. 43-74 ◽  
Author(s):  
Roger S. Debreceny ◽  
Paul L. Bowen
Keyword(s):  
Information Systems ◽  
Query Language ◽  
Accounting Information ◽  
Object Oriented ◽  
Database Systems ◽  
Control Group ◽  
Relational Schema ◽  
Accounting Information Systems ◽  
Query Performance ◽  
User Query

Object-oriented (OO) advocates assert that concepts such as generalization-specialization hierarchies (GSHs) and abstract data types (ADTs) make information systems more usable by increasing the level of abstraction of the data structure. This study analyzes the effects of GSHs and ADTs on the performance of end-users of accounting information systems. Two groups of experimental participants interactively developed Structured Query Language (SQL) queries to answer ten business questions. The control group (n = 28) used data stored in a traditional relational schema. The experimental group (n = 31) used the same data stored in an OO schema that included GSHs and ADTs. Both schemas implemented the same database accounting model of the sales cycle of a hypothetical company. Participants using the higher abstraction (OO) schema with GSHs and ADTs made fewer semantic errors than did participants using the traditional relational schema. The OO participants also required less time to formulate their queries. These results have several important implications. First, relational database vendors should continue, if not accelerate, their efforts to incorporate OO features such as GSHs and ADTs into their database systems. Second, users of accounting information systems need to improve their understanding of the implications of various data structures on their interactive queries. Third, research should investigate the effects of other abstraction mechanisms, including classification/instantiation and aggregation/decomposition, on query performance.

The Effects of User Characteristics on Query Performance in the Presence of Information Request Ambiguity

2007 ◽  
Vol 21 (1) ◽  
pp. 53-82 ◽  
Author(s):  
Neal Ashkanasy ◽  
Paul L. Bowen ◽  
Fiona H. Rohde ◽  
Chiu Yueh Alice Wu
Keyword(s):  
Personality Characteristics ◽  
Query Complexity ◽  
User Characteristics ◽  
Personality Dimensions ◽  
Query Performance ◽  
Information Request ◽  
User Personality ◽  
Syntactic Ambiguities ◽  
Information Requests ◽  
Made In

This paper investigates the effects of personality characteristics on individuals' abilities to compose queries from information requests containing various types of ambiguity. In particular, this research examines the effects of user personality characteristics on query performance in the presence of information requests that contained no extraneous, syntactic, or both extraneous and syntactic ambiguities. The results indicate that personality characteristics significantly affect users' abilities to compose accurate queries. Neuroticism, agreeableness, openness to experience, and conscientiousness significantly affected the number of errors made in the query formulations. Conscientiousness affected the length of time taken to compose the queries and neuroticism affected the confidence users had in the accuracy of their queries. Although several personality dimensions affected query performance, no significant interactions between personality dimensions and ambiguity were detected. Furthermore, both query complexity and information request ambiguity exhibited greater impacts on query performance than personality characteristics. Hence, organizations should attempt to train users to deal with query complexity and information request ambiguity before modifying their training programs for personality characteristics.

A Sliding-Window Method to Discover Recent Frequent Query Patterns from XML Query Streams

2014 ◽  
Vol 24 (06) ◽  
pp. 955-980 ◽  
Author(s):  
Tsui-Ping Chang
Keyword(s):  
Data Stream ◽  
Stream Data ◽  
Stream Mining ◽  
Memory Space ◽  
Query Performance ◽  
Mining Algorithm ◽  
Window Method ◽  
User Query ◽  
Query Patterns ◽  
User Queries

Providing efficient mining algorithm to discover recent frequent XML user query patterns is crucial, as many applications use XML to represent data in their disciplines over the Internet. These recent frequent XML user query patterns can be used to design an index mechanism or cached and thus enhance XML query performance. Several XML query pattern stream mining algorithms have been proposed to record user queries in the system and thus discover the recent frequent XML query patterns over a stream. By using these recent frequent XML query patterns, the query performance of XML data stream is improved. In this paper, user queries are modeled as a stream of XML queries and the recent frequent XML query patterns are thus mined over the stream. Data-stream mining differs from traditional data mining since its input of mining is data streams, while the latter focuses on mining static databases. To facilitate the one-pass mining process, novel schemes (i.e. XstreamCode and XstreamList) are devised in the mining algorithm (i.e. X2StreamMiner) in this paper. X2StreamMiner not only reduces the memory space, but also improves the mining performance. The simulation results also show that X2StreamMiner algorithm is both efficient and scalable. There are two major contributions in this paper. First, the novel schemes are proposed to encode and store the information of user queries in an XML query stream. Second, based on the two schemes, an efficient XML query stream mining algorithm, X2StreamMiner, is proposed to discover the recent frequent XML query patterns.

Ex Ante Evaluations of Alternate Data Structures for End User Queries

2008 ◽  
pp. 2096-2123
Author(s):  
Paul L. Bowen ◽  
Fiona H. Rohde ◽  
Jay Basford
Keyword(s):  
Data Structure ◽  
Data Structures ◽  
Weighted Average ◽  
End Users ◽  
Query Complexity ◽  
End User ◽  
Average Complexity ◽  
User Query ◽  
Ex Ante ◽  
User Queries

The data structure of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. This research develops a methodology for evaluating, ex ante, the relative desirability of alternative data structures for end user queries. This research theorizes that the data structure that yields the lowest weighted average complexity for a representative sample of information requests is the most desirable data structure for end user queries. The theory was tested in an experiment that compared queries from two different relational database schemas. As theorized, end users querying the data structure associated with the less complex queries performed better. Complexity was measured using three different Halstead metrics. Each of the three metrics provided excellent predictions of end user performance. This research supplies strong evidence that organizations can use complexity metrics to evaluate, ex ante, the desirability of alternate data structures. Organizations can use these evaluations to enhance the efficient and effective retrieval of information by creating data structures that minimize end user query complexity.

scholarly journals Analysis of Competing Data Structures: Does Ontological Clarity Produce Better End User Query Performance

2006 ◽  
Vol 7 (8) ◽  
pp. 514-544 ◽  
Author(s):  
Paul Bowen ◽  
◽  
Robert O'Farrell ◽  
Fiona Rohde ◽  
◽  
...  
Keyword(s):  
Data Structures ◽  
End User ◽  
Query Performance ◽  
User Query

A basic introduction to image processing using NIH-Image as a model

1994 ◽  
Vol 52 ◽  
pp. 392-393
Author(s):  
John Mansfield
Keyword(s):  
Image Processing ◽  
Digital Image ◽  
Image Acquisition ◽  
Digital Instrument ◽  
Novice User ◽  
Nih Image ◽  
The Past ◽  
Digital World ◽  
The World ◽  
Instrument Control

Advances in camera technology and digital instrument control have meant that in modern microscopy, the image that was, in the past, typically recorded on a piece of film is now recorded directly into a computer. The transfer of the analog image seen in the microscope to the digitized picture in the computer does not mean, however, that the problems associated with recording images, analyzing them, and preparing them for publication, have all miraculously been solved. The steps involved in the recording an image to film remain largely intact in the digital world. The image is recorded, prepared for measurement in some way, analyzed, and then prepared for presentation.Digital image acquisition schemes are largely the realm of the microscope manufacturers, however, there are also a multitude of “homemade” acquisition systems in microscope laboratories around the world. It is not the mission of this tutorial to deal with the various acquisition systems, but rather to introduce the novice user to rudimentary image processing and measurement.

Rancang Bangun Aplikasi UMN Library Catalog Menggunakan Metode Rocchio Relevance Feedback

2018 ◽  
Vol 9 (1) ◽  
pp. 9-17
Author(s):  
Marcel Bonar Kristanda ◽  
Seng Hansun ◽  
Albert Albert
Keyword(s):  
Information System ◽  
User Experience ◽  
Relevance Feedback ◽  
Android Application ◽  
Library Catalog ◽  
Relevant Result ◽  
User Query ◽  
Index Terms ◽  
Feedback Method ◽  
F Measure

Library catalog is a documentation or list of all library collections. Unfortunately, there is a problem identified in the process of searching a book inside library catalog in Universitas Multimedia Nusantara’s library information system regarding the relevant result based on user query input. This research aims to design and build a library catalog application on Android platform in order to increase the relvancy of searching result in a database using calculated Rocchio Relevance Feedback method along with user experience measurement. User experience analysis result presented a good respond with 91.18% score based by all factor and relevance value present 71.43% precision, 100% recall, and 83.33% F-Measure. Differences of relevant results between the Senayan Library Information system (SLiMS) and the new Android application ranged at 36.11%. Therefore, this Android application proved to give relevant result based on relevance rank. Index Terms—Rocchio, Relevance, Feedback, Pencarian, Buku, Aplikasi, Android, Perpustakaan.

Simulation and Performance Analysis of Tilted Time Window and Support Vector Machine Based Learning Object Ranking Method

2020 ◽  
Vol 13 (2) ◽  
pp. 153-164
Author(s):  
Narina Thakur ◽  
Deepti Mehrotra ◽  
Abhay Bansal ◽  
Manju Bala
Keyword(s):  
Support Vector Machine ◽  
Classification Accuracy ◽  
Time Window ◽  
Optimal Solution ◽  
Similarity Score ◽  
Learning Objects ◽  
Retrieval Algorithm ◽  
Support Vector ◽  
Computationally Efficient ◽  
User Query

Objective: Since the adequacy of Learning Objects (LO) is a dynamic concept and changes in its use, needs and evolution, it is important to consider the importance of LO in terms of time to assess its relevance as the main objective of the proposed research. Another goal is to increase the classification accuracy and precision. Methods: With existing IR and ranking algorithms, MAP optimization either does not lead to a comprehensively optimal solution or is expensive and time - consuming. Nevertheless, Support Vector Machine learning competently leads to a globally optimal solution. SVM is a powerful classifier method with its high classification accuracy and the Tilted time window based model is computationally efficient. Results: This paper proposes and implements the LO ranking and retrieval algorithm based on the Tilted Time window and the Support Vector Machine, which uses the merit of both methods. The proposed model is implemented for the NCBI dataset and MAT Lab. Conclusion: The experiments have been carried out on the NCBI dataset, and LO weights are assigned to be relevant and non - relevant for a given user query according to the Tilted Time series and the Cosine similarity score. Results showed that the model proposed has much better accuracy.

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