Mining the Web for Lexical Knowledge to Improve Keyphrase Extraction: Learning from Labeled and Unlabeled Data.

A journal article is often accompanied by a list of keyphrases, composed of about five to fifteen important words and phrases that capture the article’s main topics. Keyphrases are useful for a variety of purposes, including summarizing, indexing, labeling, categorizing, clustering, highlighting, browsing, and searching. The task of automatic keyphrase extraction is to select keyphrases from within the text of a given document. Automatic keyphrase extraction makes it feasible to generate keyphrases for the huge number of documents that do not have manually assigned keyphrases. Good performance on this task has been obtained by approaching it as a supervised learning problem. An input document is treated as a set of candidate phrases that must be classified as either keyphrases or non-keyphrases. To classify a candidate phrase as a keyphrase, the most important features (attributes) appear to be the frequency and location of the candidate phrase in the document. Recent work has demonstrated that it is also useful to know the frequency of the candidate phrase as a manually assigned keyphrase for other documents in the same domain as the given document (e.g., the domain of computer science). Unfortunately, this keyphrase-frequency feature is domain-specific (the learning process must be repeated for each new domain) and training-intensive (good performance requires a relatively large number of training documents in the given domain, with manually assigned keyphrases). The aim of the work described here is to remove these limitations. In this paper, I introduce new features that are conceptually related to keyphrase-frequency and I present experiments that show that the new features result in improved keyphrase extraction, although they are neither domain-specific nor training-intensive. The new features are generated by issuing queries to a Web search engine, based on the candidate phrases in the input document. The feature values are calculated from the number of hits for the queries (the number of matching Web pages). In essence, these new features are derived by mining lexical knowledge from a very large collection of unlabeled data, consisting of approximately 350 million Web pages without manually assigned keyphrases

Extraction of Keyphrases from Text: Evaluation of Four Algorithms

This report presents an empirical evaluation of four algorithms for automatically extracting keywords and keyphrases from documents. The four algorithms are compared using five different collections of documents. For each document, we have a target set of keyphrases, which were generated by hand. The target keyphrases were generated for human readers; they were not tailored for any of the four keyphrase extraction algorithms. Each of the algorithms was evaluated by the degree to which the algorithm’s keyphrases matched the manually generated keyphrases. The four algorithms were (1) the AutoSummarize feature in Microsoft’s Word 97, (2) an algorithm based on Eric Brill’s part-of-speech tagger, (3) the Summarize feature in Verity’s Search 97, and (4) NRC’s Extractor algorithm. For all five document collections, NRC’s Extractor yields the best match with the manually generated keyphrases

Competency Based Learning in Hospitality Education and Its Impact on Future Leadership Skills

In the past five years, hospitality educational programs have seen a distinct decline in enrollment from year to year (Oakley, 2016). Upon reflection of this decline, there could be many reasons, which caused a consecutive downward trajectory regarding enrollment. First, individuals are finding that a formal degree is not required for entry-level positions in the hospitality industry. Second, people are utilizing technology and videos to substitute for formal education and are finding success in the entry-level hiring process. Third, this generation does not see the value in formal education for entry-level employment. True as that might be, trends have shown that these individuals forego formal education completely and immediately enter into the workforce (Hersh, 2015). However, these individuals work for a short period of time and discover that promotion is not attainable since they lack the proper skill-set essential for leadership roles. Brownell and Chung (2001) argued that hospitality curriculum may not be offering the right knowledge and skills to individuals seeking future work and that a change must be made in higher education to address the issue. Perhaps the notion is that individuals need more than technical skills in order to succeed in their careers. If this statement is true, then putting forth changes to the curriculum in order to fill gaps in education is the first step to accomplishment. This paper examines whether competency based learning (CBL) in higher education is predictive of leadership outcomes in the hospitality industry. Within the higher education framework, competency based learning focuses on theory supported skill development and the application of concepts in scenario-based and problem-based assessments. More importantly, competency based learning emphasizes student advancement via demonstrated mastery of competencies that are specific, measureable and are learning objectives that empower students. In addition, the student learning outcomes stress competencies that include application and creation of knowledge along with the development of important skills and dispositions. Finally, CBL allows students to learn skills vital to leadership success in the hospitality industry

Mind and autism spectrum disorders: A Theory-of-Mind continuum model and typology developed from Theory-of Mind as subjectively experienced and objectively understood

This study defines Theory-of-Mind as the ability to experience one’s own mind and understand the minds of others to the extent necessary to make sense of human behaviour and the world. Since the concept of Theory-of-Mind was first applied to people with ASD (Baron-Cohen, Leslie & Frith, 1985), lack of Theory-of-Mind has been used to explain their cognitive difficulties (National Research Council, 2003), along with social, communicative and imaginative impairments (Frith, Happé & Siddons, 1994). Previous studies have tended to think of Theory-of-Mind in terms of a simple binary of deficit or credit; to exclude the voices of people with ASD; to emphasise the cognitive aspects of Theory-of-Mind over its affective aspects; and to emphasise understanding the minds of others over experiencing one’s own mind. This study aims to address these issues by investigating Theory-of-Mind as subjectively experienced by students with ASD and objectively understood by their teachers. It is the first attempt in the study of Theory-of-Mind to include the voices of individuals with ASD along with the professional views of their teachers. This study takes an interdisciplinary approach, supported by philosophy of mind and special education. A grounded theory approach and a mixed methods research design combine to build and strengthen a theory of Theory-of-Mind. For Theory-of-Mind as subjectively experienced, 20 senior secondary and post secondary school students with ASD from Republic of Korea were interviewed and student-produced documents were reviewed to draw out their inner experiences. The Korean Wechsler Adult Intelligence Scale and the Korean Vineland Social Maturity Scale were employed to assess IQ and social competence. For Theory-of-Mind as objectively understood, their teachers’ beliefs regarding their students with ASD were sought through in-depth interviews, a review of teacher-produced documents and administration of a newly developed Teacher Questionnaire. This study reports differences between Theory-of-Mind as subjectively experienced and objectively observed, and variations within the components of Theory-of-Mind. The role of imagination in Theory-of-Mind and the relationships between Theory-of-Mind components, IQ and social competence are discussed. As a result, a Theory-of-Mind continuum model and Theory-of-Mind Typology is proposed