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In his study - Evaluating and Selecting a Property Management System - by Galen Collins, Assistant Professor, School of Hotel and Restaurant Management, Northern Arizona University, Assistant Professor Collins states briefly at the outset: “Computerizing a property requires a game plan. Many have selected a Property Management System without much forethought and have been unhappy with the final results. The author discusses the major factors that must be taken into consideration in the selection of a PMS, based on his personal experience.” Although, this article was written in the year 1988 and some information contained may be dated, there are many salient points to consider. “Technological advances have encouraged many hospitality operators to rethink how information should be processed, stored, retrieved, and analyzed,” offers Collins. “Research has led to the implementation of various cost-effective applications addressing almost every phase of operations,” he says in introducing the computer technology germane to many PMS functions. Professor Collins talks about the Request for Proposal, its conditions and its relevance in negotiating a PMS system. The author also wants the system buyer to be aware [not necessarily beware] of vendor recommendations, and not to rely solely on them. Exercising forethought will help in avoiding the drawback of purchasing an inadequate PMS system. Remember, the vendor is there first and foremost to sell you a system. This doesn’t necessarily mean that the adjectives unreliable and unethical are on the table, but do be advised. Professor Collins presents a graphic outline for the Weighted Average Approach to Scoring Vendor Evaluations. Among the elements to be considered in evaluating a PMS system, and there are several analyzed in this essay, Professor Collins advises that a perspective buyer not overlook the service factor when choosing a PMS system. Service is an important element to contemplate. “In a hotel environment, the special emphasis should be on service. System downtime can be costly and aggravating and will happen periodically,” Collins warns. Professor Collins also examines the topic of PMS system environment; of which the importance of such a factor should not be underestimated. “The design of the computer system should be based on the physical layout of the property and the projected workloads. The heart of the system, housed in a protected, isolated area, can support work stations strategically located throughout the property,” Professor Collins provides. A Property Profile Description is outlined in Table 1. The author would also point out that ease-of-operation is another significant factor to think about. “A user-friendly software package allows the user to easily move through the program without encountering frustrating obstacles,” says Collins. “Programs that require users to memorize abstract abbreviations, codes, and information to carry out standard routines should be avoided,” he counsels.

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The increasing amount of available semistructured data demands efficient mechanisms to store, process, and search an enormous corpus of data to encourage its global adoption. Current techniques to store semistructured documents either map them to relational databases, or use a combination of flat files and indexes. These two approaches result in a mismatch between the tree-structure of semistructured data and the access characteristics of the underlying storage devices. Furthermore, the inefficiency of XML parsing methods has slowed down the large-scale adoption of XML into actual system implementations. The recent development of lazy parsing techniques is a major step towards improving this situation, but lazy parsers still have significant drawbacks that undermine the massive adoption of XML. Once the processing (storage and parsing) issues for semistructured data have been addressed, another key challenge to leverage semistructured data is to perform effective information discovery on such data. Previous works have addressed this problem in a generic (i.e. domain independent) way, but this process can be improved if knowledge about the specific domain is taken into consideration. This dissertation had two general goals: The first goal was to devise novel techniques to efficiently store and process semistructured documents. This goal had two specific aims: We proposed a method for storing semistructured documents that maps the physical characteristics of the documents to the geometrical layout of hard drives. We developed a Double-Lazy Parser for semistructured documents which introduces lazy behavior in both the pre-parsing and progressive parsing phases of the standard Document Object Model's parsing mechanism. The second goal was to construct a user-friendly and efficient engine for performing Information Discovery over domain-specific semistructured documents. This goal also had two aims: We presented a framework that exploits the domain-specific knowledge to improve the quality of the information discovery process by incorporating domain ontologies. We also proposed meaningful evaluation metrics to compare the results of search systems over semistructured documents.