Online discovery of similarity mappings

We consider the problem of choosing, sequentially, a map which assigns elements of a set A to a few elements of a set B. On each round, the algorithm suffers some cost associated with the chosen assignment, and the goal is to minimize the cumulative loss of these choices relative to the best map on the entire sequence. Even though the offline problem of finding the best map is provably hard, we show that there is an equivalent online approximation algorithm, Randomized Map Prediction (RMP), that is efficient and performs nearly as well. While drawing upon results from the "Online Prediction with Expert Advice" setting, we show how RMP can be utilized as an online approach to several standard batch problems. We apply RMP to online clustering as well as online feature selection and, surprisingly, RMP often outperforms the standard batch algorithms on these problems.

Enlightening, balancing and transcending entrepreneurial orientation : the 4th annual EO3 research PDW

Entrepreneurial Orientation (EO) has a 30 year history as one of the most used concepts in entrepreneurship research. “Recent attention in formal sessions at the Academy of Management conference programs confirm Entrepreneurial Orientation as a primary construct with a majority of Entrepreneurship Division sponsored sessions devoted to studies using EO related measures”, as reported by the 2010 division program chair, Per Davidson (Roberts, 2010: 9). However, questions continue to be raised concerning over-dependence on parts of one strategic scale, possible inappropriate or under-theorized adaptations, and the lack of theoretical development on application and performance variance in emergent, organizational, and socioeconomic settings. One recent area of investigation in analysis, methods, theory and application concerns an “EO gestalt”, focusing on the family of EO-related measures and theory, rather than on one or more dimensions, in order to explore the theory and process of the Entrepreneurial Orientation phenomenon. The goals of the 4th Annual EO3 PDW are to enlighten researchers on the development of Entrepreneurial Orientation theory and related scales, balance the use of Entrepreneurial Orientation current knowledge with new research frontiers suggested by EO3 scholars’ questions, and transcend boundaries in the discoveries undertaken in the shared interdisciplinary and cross-cultural research agenda currently developing for Entrepreneurial Orientation concepts. Going into its forth year, the EO3 PDW has been pivotal in formalizing discussion, pushing research forward, and gaining insights from experienced and cutting edge scholars, as it provides a point of reference for coalescing research questions and findings surrounding this important concept.

Unpacking the entrepreneurial process : A step-by-step guide to a successful venture in the entertainment industry

Unpacking the Entrepreneurial Process: A Step-by-Step Guide to a Successful Venture in the Entertainment Industry introduces a step-by-step guide to either students, entrepreneurs and intrapreneurs to fully understand the necessary steps to both unleash their entrepreneurial capabilities and to foster the development of new ones.

Entrepreneurial becoming : an educational pathway out of poverty

This paper reports a longitudinal analysis of 20 necessity driven micro-entrepreneurs operating in Beira, Central Mozambique, who received funding and training from the same NGO to establish or grow their business activities and reports the development of these entrepreneurs in terms of their acquired entrepreneurial potential for long-term success. The results indicate there is a process of entrepreneurial becoming that is not just about access to finance but especially learning and, when successful, this process supports the transformation of survival micro-enterprises into entrepreneurial micro-businesses. The concept of ‘becoming’ contains an implicit temporal dimension. Becoming suggests a transformation over time: a change from what one is already. In this study, we witness a significant change in understanding how a business needs to operate, in recognizing opportunities, thinking more creatively, and building self-confidence.

A Virtual Evaluation Track for Cross Language Link Discovery

The Wikipedia has become the most popular online source of encyclopedic information. The English Wikipedia collection, as well as some other languages collections, is extensively linked. However, as a multilingual collection the Wikipedia is only very weakly linked. There are few cross-language links or cross-dialect links (see, for example, Chinese dialects). In order to link the multilingual-Wikipedia as a single collection, automated cross language link discovery systems are needed – systems that identify anchor-texts in one language and targets in another. The evaluation of Link Discovery approaches within the English version of the Wikipedia has been examined in the INEX Link the-Wiki track since 2007, whilst both CLEF and NTCIR emphasized the investigation and the evaluation of cross-language information retrieval. In this position paper we propose a new virtual evaluation track: Cross Language Link Discovery (CLLD). The track will initially examine cross language linking of Wikipedia articles. This virtual track will not be tied to any one forum; instead we hope it can be connected to each of (at least): CLEF, NTCIR, and INEX as it will cover ground currently studied by each. The aim is to establish a virtual evaluation environment supporting continuous assessment and evaluation, and a forum for the exchange of research ideas. It will be free from the difficulties of scheduling and synchronizing groups of collaborating researchers and alleviate the necessity to travel across the globe in order to share knowledge. We aim to electronically publish peer-reviewed publications arising from CLLD in a similar fashion: online, with open access, and without fixed submission deadlines.

Evaluation framework for focused link discovery

Information has no value unless it is accessible. Information must be connected together so a knowledge network can then be built. Such a knowledge base is a key resource for Internet users to interlink information from documents. Information retrieval, a key technology for knowledge management, guarantees access to large corpora of unstructured text. Collaborative knowledge management systems such as Wikipedia are becoming more popular than ever; however, their link creation function is not optimized for discovering possible links in the collection and the quality of automatically generated links has never been quantified. This research begins with an evaluation forum which is intended to cope with the experiments of focused link discovery in a collaborative way as well as with the investigation of the link discovery application. The research focus was on the evaluation strategy: the evaluation framework proposal, including rules, formats, pooling, validation, assessment and evaluation has proved to be efficient, reusable for further extension and efficient for conducting evaluation. The collection-split approach is used to re-construct the Wikipedia collection into a split collection comprising single passage files. This split collection is proved to be feasible for improving relevant passages discovery and is devoted to being a corpus for focused link discovery. Following these experiments, a mobile client-side prototype built on iPhone is developed to resolve the mobile Search issue by using focused link discovery technology. According to the interview survey, the proposed mobile interactive UI does improve the experience of mobile information seeking. Based on this evaluation framework, a novel cross-language link discovery proposal using multiple text collections is developed. A dynamic evaluation approach is proposed to enhance both the collaborative effort and the interacting experience between submission and evaluation. A realistic evaluation scheme has been implemented at NTCIR for cross-language link discovery tasks.

Cognitive factors in entrepreneurial strategic decision making

Research on strategic decision making (SDM) has proliferated in the last decades. Most of the studies however, focus on the process and content of SDM, whereas relatively little interest was awarded to the factors associated with the decision maker influencing SDM. Moreover, most of the research on SDM focuses on large multinationals and little to no research is available that studies the ways in which entrepreneurs make strategic choices. The present study reviews the entrepreneurial traits that influence SDM. These traits are selected by analyzing the literature on the differences between entrepreneurs and managers, under the assumption that these factors are the most indicative for the particularities of entrepreneurial SDM. One of the most important theoretical propositions resulting from this analysis concerns the mediating role of cognitive complexity in the relation between these entrepreneurial traits and SDM outcomes. Directions for further research emerging from this conceptualization are identified and discussed.

An ontology-based mining approach for user search intent discovery

Discovering proper search intents is a vi- tal process to return desired results. It is constantly a hot research topic regarding information retrieval in recent years. Existing methods are mainly limited by utilizing context-based mining, query expansion, and user profiling techniques, which are still suffering from the issue of ambiguity in search queries. In this pa- per, we introduce a novel ontology-based approach in terms of a world knowledge base in order to construct personalized ontologies for identifying adequate con- cept levels for matching user search intents. An iter- ative mining algorithm is designed for evaluating po- tential intents level by level until meeting the best re- sult. The propose-to-attempt approach is evaluated in a large volume RCV1 data set, and experimental results indicate a distinct improvement on top precision after compared with baseline models.

Relevance feature discovery for text analysis

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term- based ones in describing user preferences, but many experiments do not support this hypothesis. This research presents a promising method, Relevance Feature Discovery (RFD), for solving this challenging issue. It discovers both positive and negative patterns in text documents as high-level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the high-level features. The thesis also introduces an adaptive model (called ARFD) to enhance the exibility of using RFD in adaptive environment. ARFD automatically updates the system's knowledge based on a sliding window over new incoming feedback documents. It can efficiently decide which incoming documents can bring in new knowledge into the system. Substantial experiments using the proposed models on Reuters Corpus Volume 1 and TREC topics show that the proposed models significantly outperform both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and other pattern-based methods.

Mobile applications of focused link discovery

Interaction with a mobile device remains difficult due to inherent physical limitations. This dif-ficulty is particularly evident for search, which re-quires typing. We extend the One-Search-Only search paradigm by adding a novel link-browsing scheme built on top of automatic link discovery. A prototype was built for iPhone and tested with 12 subjects. A post-use interview survey suggests that the extended paradigm improves the mobile information seeking experience.

International entrepreneurial values elicited through repertory test and laddering analysis : an SME, internet-enabled tourism perspective

This study explores the international entrepreneurial values influencing the intensity of Internet use in the internationalization process of small to medium sized enterprises (SMEs), within the Australian tourism industry. The findings point to a relationship between the values of international entrepreneurs and the inclination of the firm to develop and initiate international activity. And so, this study endeavors to offer insight into issues that remain unresolved in existing tourism and international entrepreneurship (IE) literature. Two effective but underutilized qualitative methods were used in this study to identify the values of international entrepreneurs. They are repertory test and laddering analysis.