Arif Ur Rahman

SIARD archive browser

SIARD Suite enables us to preserve a relational database in an open format. It migrates a relational database to SIARD format and preserves technical and contextual metadata along with the primary data ensuring long term accessibility. This paper introduces a web application, the SIARD Archive Browser, which allows operations on the archive such as searching for a specific record, counting records in a table containing a keyword, sorting by a column and making joins. In many use cases, the application avoids the need to load a preserved database to a DBMS.

Trajectory Mining Using Uncertain Sensor Data

Trajectory mining is an interesting data mining problem. Traditionally, it is either assumed that the time-ordered location data recorded as trajectories are either deterministic or that the uncertainty, e.g., due to equipment or technological limitations, is removed by incorporating some pre-processing routines. Thus, the trajectories are processed as deterministic paths of mobile object location data. However, it is important to understand that the transformation from uncertain to deterministic trajectory data may result in the loss of information about the level of confidence in the recorded events. Probabilistic databases offer ways to model uncertainties using possible world semantics. In this paper, we consider uncertain sensor data and transform this to probabilistic trajectory data using pre-processing routines. Next, we model this data as tuple level uncertain data and propose dynamic programming-based algorithms to mine interesting trajectories. A comprehensive empirical study is performed to evaluate the effectiveness of the approach. The results show that the trajectories could be modeled and worked as probabilistic data and that the results could be computed efficiently using dynamic programming.

Normalizing digital news-stories for preservation

Preserving news stories may be important because of various reasons like they provide detailed information about events and they may be used for research purposes in the long term. However, the news stories published online are in danger because of reasons like constant change in the technologies used to publish information and the formats for publication. Certain institutions or individuals may be interested in preserving news stories related to a particular event or topic. The stories should be collected from various online newspapers and preserved for the long term. The major issue in the preservation process is that newspapers use different formats for online publication of the stories. The paper presents a tool which is developed to addresses the issue. The tool facilitates users in the extraction of news stories from various online newspapers and migration to a normalized format.

Term-Based Approach for Linking Digital News Stories

The World Wide Web has become a platform for news publication in the past few years. Many television channels, magazines and newspapers have started publishing digital versions of the news stories online. It is observed that recommendation systems can automatically process lengthy articles and identify similar articles to readers based on a predefined criteria i.e. collaborative filtering, content-based filtering approach. The paper presents a content-based similarity measure for linking digital news stories published in various newspapers during the preservation process. The study compares similarity of news articles based on human judgment with a similarity value computed automatically using common ratio measure for stories. The results are generalized by defining a threshold value based on multiple experimental results using the proposed approach.

Evaluation of Navigational Aspects of Moodle

Learning Management System (LMS) is an effective platform for communication and collaboration among teachers and students to enhance learning. These LMSs are now widely used in both conventional and virtual and distance learning paradigms. These LMSs have various limitations as identified in the existing literature, including poor learning content, use of appropriate technology and usability issues. Poor usability leads to the distraction of users. Literature covers many aspects of usability evaluation of LMS. However, there is less focus on navigational issues. Poor navigational can lead to disorientation and cognitive overload of the users of any Web application. For this reason, we have proposed a navigational evaluation framework to evaluate the navigational structure of the LMS. We have applied this framework to evaluate the navigational structure of Moodle. We conducted a survey among students and teachers of two leading universities in Pakistan, where Moodle is in use. This work summarizes the survey results and proposes guidelines to improve the usability of Moodle based on the feedback received from its users.

A Novel Approach for Ranking Images Using User and Content Tags

In this study, a tag and content-based ranking algorithm is proposed for image retrieval that uses the metadata of images as well as the visual features of images, also known as “visual words” to retrieve more relevant images. Thus, making the retrieval process more accurate than the keyword-based retrieval approaches. Both tag and content-based image retrieval techniques have their own advantages and disadvantages. By combining the two, their disadvantages have been offset. The proposed system has been developed to bridge the gap between the existing techniques and the desired user requirements. Initially, the system extracts the metadata of images and stores them into a custom designed dictionary dataset. Then, the system creates a visual vocabulary and trains a classifier on a dataset of images belonging to different categories. Next, for any given userquery, the system makes a decision to display a class of images that best matches the query. These class images are processed in a way that we compute the relevance scores for each image and display the result based on the score.

Database Preservation: The DBPreserve Approach

In many institutions relational databases are used as a tool for managing information related to day to day activities. Institutions may be required to keep the information stored in relational databases accessible because of many reasons including legal requirements and institutional policies. However, the evolution in technology and change in users with the passage of time put the information stored in relational databases in danger. In the long term the information may become inaccessible when the operating system, database management system or the application software is not available any more or the contextual information not stored in the database may be lost thus affecting the authenticity and understandability of the information. This paper presents an approach for preserving relational databases for the long-term. The proposal involves migrating a relational database to a dimensional model which is simple to understand and easy to write queries against. Practical transformation rules are developed by carrying out multiple case studies. One of the case studies is presented as a running example in the paper. Systematic implementation of the rules ensures no loss of information in the process except for the unwanted details. The database preserved using the approach is converted to an open format but may be reloaded to a database management system in the long-term.