Search results

The purpose of this paper is to convert real-world raster data into vector format and evaluate loss of accuracy in the conversion process. Open-source Geographic Information System (GIS) is used in this process and system resource utilizations were measured for conversion and accuracy analysis methods. Shape complexity attributes were analyzed in co-relation to the observed conversion errors.

The paper empirically evaluated the challenges and overheads involved in the format conversion algorithms available in open-source GIS with real-world land use and land cover (LULC) map data of India. Across the different LULC categories, geometric errors of varying density were observed in Quantum GIS (QGIS) algorithm. Area extents of original raster data were compared to the vector forms and the shape attributes such as average number of vertices and shape irregularity were evaluated to explore the possible correlation.

The results indicate that Geographic Resources Analysis Support System provides near error-free conversion algorithm. At the same time, the overall time taken for the conversion and the system resource utilizations were optimum as compared to the QGIS algorithm. Higher vector file sizes were generalized and accuracy loss was tested.

Complete shape complexity analysis could not be achieved, as the weight factor for the irregularity of the shapes is to be varied based on the demography as well as on the LULC category.

Because of the higher system resource requirements of topological checker tool, positional accuracy checks for the converted objects could not be completed.

This paper addresses the need of accuracy analysis of real-world spatial data conversions from raster to vector format along with experimental setups challenges and impact of shape complexity.

To share the experiences gained during the migration of library data from one library management system (LibSys™) to another (e‐Granthalaya™).

The paper describes the step‐by‐step approach taken to migrate the existing library data to the new software. The paper also discusses the peculiarities of the source software from which data were converted and the practical approach adopted in solving the problems faced during the conversion.

During the process of the conversion of the library data from one software to another many lessons have been learned. These lessons and experiences will be useful for us in the future to import/export the data from other software such as MINISIS, CDS/ISIS, TECHLIB PLUS, etc. being used in Indian libraries. Moreover, the switch over from one software to another is also useful for the libraries as the existing data are refined and cleaned during the conversion process.

The authors share the lessons learned during the conversion process and hope that these will be useful to others in migration of data.

Automation planners need to view retrospective conversion from an informed and balanced perspective. They must consider: 1) the technical dimensions of retrospective conversion, 2) the appropriate standards to employ, 3) the proper relationship of conversion activities to the entire automation project, and 4) options available for converting a bibliographic database into machine‐readable format. Six prominent consultants provide important advice on this topic.

Purchase conversion prediction aims to improve user experience and convert visitors into real buyers to drive sales of firms; however, the total conversion rate is low, especially for e-retailers. To date, little is known about how e-retailers can scientifically detect users' intents within a purchase conversion funnel during their ongoing sessions and strategically optimize real-time marketing tactics corresponding to dynamic intent states. This study mainly aims to detect a real-time state of the conversion funnel based on graph theory, which refers to a five-class classification problem in the overt real-time choice decisions (RTCDs)—click, tag-to-wishlist, add-to-cart, remove-from-cart and purchase—during an ongoing session.

The authors propose a novel graph-theoretic framework to detect different states of the conversion funnel by identifying a user's unobserved mindset revealed from their navigation process graph, namely clickstream graph. First, the raw clickstream data are identified into individual sessions based on a 30-min time-out heuristic approach. Then, the authors convert each session into a sequence of temporal item-level clickstream graphs and conduct a temporal graph feature engineering according to the basic, single-, dyadic- and triadic-node and global characteristics. Furthermore, the synthetic minority oversampling technique is adopted to address with the problem of classifying imbalanced data. Finally, the authors train and test the proposed approach with several popular artificial intelligence algorithms.

The graph-theoretic approach validates that users' latent intent states within the conversion funnel can be interpreted as time-varying natures of their online graph footprints. In particular, the experimental results indicate that the graph-theoretic feature-oriented models achieve a substantial improvement of over 27% in line with the macro-average and micro-average area under the precision-recall curve, as compared to the conventional ones. In addition, the top five informative graph features for RTCDs are found to be Transitivity, Edge, Node, Degree and Reciprocity. In view of interpretability, the basic, single-, dyadic- and triadic-node and global characteristics of clickstream graphs have their specific advantages.

The findings suggest that the temporal graph-theoretic approach can form an efficient and powerful AI-based real-time intent detecting decision-support system. Different levels of graph features have their specific interpretability on RTCDs from the perspectives of consumer behavior and psychology, which provides a theoretical basis for the design of computer information systems and the optimization of the ongoing session intervention or recommendation in e-commerce.

To the best of the authors' knowledge, this is the first study to apply clickstream graphs and real-time decision choices in conversion prediction and detection. Most studies have only meditated on a binary classification problem, while this study applies a graph-theoretic approach in a five-class classification problem. In addition, this study constructs temporal item-level graphs to represent the original structure of clickstream session data based on graph theory. The time-varying characteristics of the proposed approach enhance the performance of purchase conversion detection during an ongoing session.

This paper examines the problem many researchers experience of having to spend much time rekeying records obtained from external online and CD‐ROM databases into their own personal databases on personal computers (PC). An overview of the possibilities for electronic transfer of such records is given. For a university library and information centre the need for a multi‐purpose reformatting program, capable of converting record formats of many diverse databases to a multitude of personal database formats, is demonstrated. One such program, HEADFORM, is used to test record conversion from one CD‐ROM and four online databases to three researchers' personal databases on PC, and to determine approximate time savings by transferring such records electronically instead of manually. Results show that, with a few limitations, records from online and CD‐ROM databases can be converted successfully to the formats required by these three personal database systems, and that significant time savings are possible by electronic transfer of converted records, instead of rekeying these records into personal databases.

The library metadata of the twenty-first century is moving toward a linked data model. BIBFRAME, which stands for Bibliographic Framework Initiative, was launched in 2011 with the goal to make bibliographic descriptions sharable and interoperable on the web. Since its inception, BIBFRAME development has made remarkable progress. The focus of BIBFRAME discussions has now shifted from experimentation to implementation. The library community is collaborating with all stakeholders to build the infrastructure for BIBFRAME production in order to provide the environment where BIBFRAME data can be easily created, reused, and shared. This chapter addresses library community's BIBFRAME endeavors, with the focus on Library of Congress, Program for Cooperative Program, Linked Data for Production Phase 2, and OCLC. This chapter discusses BIBFRAME's major differences from the MARC standard with the hope of helping metadata practitioners get a general understanding of the future metadata activity. While the BIBFRAME landscape is beginning to take shape and its practical implications are beginning to develop, it is anticipated that MARC records will continue to be circulated for the foreseeable future. Upcoming multistandard metadata environments will bring new challenges to metadata practitioners, and this chapter addresses the required knowledge and skills for this transitional and multistandard metadata landscape. Finally, this chapter explores BIBFRAME's remaining challenges to realize the BIBFRAME production environment and asserts that BIBFRAME's ultimate goal is to deliver a value-added next-web search experience to our users.

The City of Melbourne seeks to retrofit 1,200 CBD properties by 2020 as part of the strategy to become carbon neutral, whilst Amsterdam aims to cut CO₂ emissions 40 per cent by 2025. Oversupply in the Amsterdam office market makes conversion to residential use viable. In examining converted buildings in Amsterdam and the Melbourne CBD typical attributes of converted stock can be identified to target retrofit measures. This paper seeks to focus on these initiatives.

In Amsterdam five case studies were undertaken to reveal and define building attributes that explain the viability of these conversions. On the other hand, the Melbourne study was based on a database assembled containing all Melbourne CBD office building adaptations carried out between 1998 and 2008. The research analysed the conversion of office buildings and the scope for sustainable retrofit evaluating a limited number of attributes known to be important in adaptation.

The outcomes of this research showed similarities and differences in scope, which are relevant to all urban areas where adaptation of office buildings can mitigate the impacts of climate change and enhance a city for another generation of citizens and users.

The outcomes highlight the property attributes that explain conversion viability and that are most strongly associated with conversions. In addition the research identifies some sustainability measures that are possible with this type of stock.

The paper compares and contrasts qualitative data from a small sample of buildings in Amsterdam with quantitative data from a census of all change of use adaptations in Melbourne from 1998 to 2008. The contrasting approaches make it possible both to explain the driving forces of adaptations and to deliver statistical evidence of what is described in the case studies. Despite the differing approaches it is possible to compare and contrast the attributes of properties from both cities.

To share the experiences in data migration of the KFUPM Library with libraries planning to move from legacy systems such as DOBIS/LIBIS to third‐generation systems.

A detailed analysis of DOBIS/LIBIS data structure, data extraction, including data mining, and data conversion of bibliographic, non‐bibliographic and bilingual data was carried out to provide maximum information to libraries about the complexities of source data and how to overcome them.

The majority of the problems came from the lack of full MARC support in DOBIS/LIBIS and because of some local practices.

The study is limited to the KFUPM library experience in data conversion from DOBIS/LIBIS to Horizon.

This study will have implications for libraries still operating under legacy systems. They are expected to be informed by the KFUPM library experience and hopefully will work on migrating to a new system sooner than later. On the other hand, libraries in the Middle East will receive encouragement from the authors' experience and will feel some relief that, despite the complexities of bilingual data, they have a good example to follow.

This is the first study of data conversion in the Middle East and has enormous value for libraries still struggling with legacy systems. Following the KFUPM library example, they can now plan for their own system and data migration.

The National Bibliographic Information Network (NBINet) in Taiwan is a bibliographic database established on 30 October 1991 and maintained by the National Central Library. In 1998 there were 26 member libraries and 70 non‐member libraries in NBINet, which is considered a comprehensive database for Chinese studies worldwide and contains more than 1.6 million bibliographic records. This paper discusses the problems encountered in the establishment of NBINet and the solutions related to computers and networks, NBINet’s utilization on the Internet, and user expectations of NBINet.