Bulkloading and Maintaining XML Documents

The popularity of XML as a exchange and storage format brings about massive amounts of documents to be stored, maintained and analyzed -- a challenge that traditionally has been tackled with Database Management Systems (DBMS). To open up the content of XML documents to analysis with declarative query languages, efficient bulk loading techniques are necessary. Database technology has traditionally been offering support for these tasks but yet falls short of providing efficient automation techniques for the challenges that large collections of XML data raise. As storage back-end, many applications rely on relational databases, which are designed towards large data volumes. This paper studies the bulk load and update algorithms for XML data stored in relational format and outlines opportunities and problems. We investigate both (1) bulk insertion and deletion as well as (2) updates in the form of edit scripts which heavily use pointer-chasing techniques which often are considered orthogonal to the algebraic operations relational databases are optimized for. To get the most out of relational database systems, we show that one should make careful use of edit scripts and replace them with bulk operations if more than a very small portion of the database is updated. We implemented our ideas on top of the Monet Database System and benchmarked their performance

Acoi: A System for Indexing Multimedia Objects

The explosion of the number of Web pages also leads to countless accessible multimedia objects. Their abundance makes the Internet an interesting application for multimedia retrieval systems. Many search engines are going about to supply some retrieval functionality for independent retrieval of these objects. However, most of these multimedia search engines aim at a fixed set of multimedia index attributes. The Acoi system provides an extensible framework for retrieving multimedia objects of any type on basis of their content, based on both low-level features and high-level concepts, and context

Storing XML Documents in Databases

The authors introduce concepts for loading large amounts of XML documents into databases where the documents are stored and maintained. The goal is to make XML databases as unobtrusive in multi-tier systems as possible and at the same time provide as many services defined by the XML standards as possible. The ubiquity of XML has sparked great interest in deploying concepts known from Relational Database Management Systems such as declarative query languages, transactions, indexes and integrity constraints. This chapter presents now bulkloading is done in Monet XML, a main memory XML database system, and evaluates the cost of bulkloading and bulk deletion with respect to strategies which base on insertion and deletion of individual nodes. Additionally, we survey the applicability of the techniques to a wider class of XML storage schemas

Indexing real-world data using semi-structured documents

We address the problem of deriving meaningful semantic index information for a multi-media database using a semi-structured docu-ment model. We show how our framework, called {em feature grammars, can be used to (1)~exploit third-party interpretation modules for real-world unstructured components, and (2)~use context-free grammars to convert such poorly or unstructured input to semi-structured output. The basic idea is to enrich context-free grammars with special symbols called detectors, which provide for the necessary structure {em just-in-time to satisfy a parser look-ahead. A prototype implementation has been constructed in the Acoi project to demonstrate the feasibility of this approach for indexing both images and audio documents

Querying XML Documents Made Easy: Nearest Concept Queries

Due to the ubiquity and popularity of XML, users often are in the following situation: they want to query XML documents which contain potentially interesting information but they are unaware of the mark-up structure that is used. For example, it is easy to guess the contents of an XML bibliography file whereas the mark-up depends on the methodological, cultural and personal background of the author(s). Nonetheless, it is this hierarchical structure that forms the basis of XML query languages. In this paper we exploit the tree structure of XML documents to equip users with a powerful tool, the meet operator, that lets them query databases with whose content they are familiar, but without requiring knowledge of tags and hierarchies. Our approach is based on computing the lowest common ancestor of nodes in the XML syntax tree: eg, given two strings, we are looking for nodes whose offspring contains these two strings. The novelty of this approach is that the result type is unknown at query formulation time and dependent on the database instance. If the two strings are an author's name and a year, mainly publications of the author in this year are returned. If the two strings are numbers the result mostly consists of publications that have the numbers as year or page numbers. Because the result type of a query is not specified by the user we refer to the lowest common ancestor as nearest concept We also present a running example taken from the bibliography domain, and demonstrate that the operator can be implemented efficiently

Allocation and Productivity of Time in New Ventures of Female and Male Entrepreneurs

[Please note that there exists an updated version of this publication at http://hdl.handle.net/1765/8989] This study investigates the factors explaining the number of hours invested in new ventures, making a distinction between the effect of preference for work time versus leisure time and that of productivity of work time. Using data of 1247 Dutch entrepreneurs, we find that time invested in the business is determined by various aspects of human, financial and social capital, availability of other income, outsourcing, side activities and gender. We show that some of the identified factors relate to preferences and others to productivity. Women appear to invest less time in the business as a result of a range of indirect productivity effects

Allocation and Productivity of Time in New Ventures of Female and Male Entrepreneurs

This paper investigates time allocation decisions in new ventures of female and male entrepreneurs using a model that distinguishes between effects of preferences and productivity on the number of working hours. Using data of 1,158 entrepreneurs we find that the preference for work time in new ventures relates to start-up motivation, propensity to take risk and availability of other income. Productivity of work time relates to human, financial and social capital endowments and the prevalence of outsourcing activities. This study also evaluates actual profit effects one year after start-up. We find that on average women invest less time in the business than men. This can be attributed to both a lower preference for work time (driven by risk aversion and availability of other income) and a lower productivity per hour worked (due to lower endowments of human, social and financial capital)

Does Entrepreneurship Reduce Unemployment?

The relationship between unemployment and entrepreneurship has been shrouded with ambiguity. There is assumed to be a two-way causation between changes in the level of entrepreneurship and that of unemployment-- a "Schumpeter" effect of entrepreneurship reducing unemployment and a "refugee" or "shopkeeper" effect of unemployment stimulating entrepreneurship. The purpose of this paper is to try to reconcile the ambiguities found in the relationship between unemployment and entrepreneurship. We do this by introducing a two equation model where changes in unemployment and in the number of business owners are linked to subsequent changes in those variables for a panel of 23 OECD countries over the period 1974-1998. The existence of two distinct and separate relationships between unemployment and entrepreneurship is identified including significant "Schumpeter" and "refugee" effects