A comparison of pseudo-paper and paper prototyping methods for mobile evaluations

The research presented in this paper is part of an ongoing investigation into how best to support meaningful lab-based usability evaluations of mobile technologies. In particular, we report on a comparative study of (a) a standard paper prototype of a mobile application used to perform an early-phase seated (static) usability evaluation, and (b) a pseudo-paper prototype created from the paper prototype used to perform an early-phase,contextually-relevant, mobile usability evaluation. We draw some initial conclusions regarding whether it is worth the added effort of conducting a usability evaluation of a pseudo-paper prototype in a contextually-relevant setting during early-phase user interface development.

Self-training from labeled features for sentiment analysis

Sentiment analysis concerns about automatically identifying sentiment or opinion expressed in a given piece of text. Most prior work either use prior lexical knowledge defined as sentiment polarity of words or view the task as a text classification problem and rely on labeled corpora to train a sentiment classifier. While lexicon-based approaches do not adapt well to different domains, corpus-based approaches require expensive manual annotation effort. In this paper, we propose a novel framework where an initial classifier is learned by incorporating prior information extracted from an existing sentiment lexicon with preferences on expectations of sentiment labels of those lexicon words being expressed using generalized expectation criteria. Documents classified with high confidence are then used as pseudo-labeled examples for automatical domain-specific feature acquisition. The word-class distributions of such self-learned features are estimated from the pseudo-labeled examples and are used to train another classifier by constraining the model's predictions on unlabeled instances. Experiments on both the movie-review data and the multi-domain sentiment dataset show that our approach attains comparable or better performance than existing weakly-supervised sentiment classification methods despite using no labeled documents.

Learning sentiment classification model from labeled features

We propose a novel framework where an initial classifier is learned by incorporating prior information extracted from an existing sentiment lexicon. Preferences on expectations of sentiment labels of those lexicon words are expressed using generalized expectation criteria. Documents classified with high confidence are then used as pseudo-labeled examples for automatical domain-specific feature acquisition. The word-class distributions of such self-learned features are estimated from the pseudo-labeled examples and are used to train another classifier by constraining the model's predictions on unlabeled instances. Experiments on both the movie review data and the multi-domain sentiment dataset show that our approach attains comparable or better performance than exiting weakly-supervised sentiment classification methods despite using no labeled documents.

Real teams or pseudo teams? The changing landscape needs a better map

Commentary on focal article by Tannenbaum et al., Teams are changing: Are research and practice evolving fast enough?

“I didn’t mean to steal someone else’s words!”:a forensic linguistic approach to detecting intentional plagiarism

The concept of plagiarism is not uncommonly associated with the concept of intellectual property, both for historical and legal reasons: the approach to the ownership of ‘moral’, nonmaterial goods has evolved to the right to individual property, and consequently a need was raised to establish a legal framework to cope with the infringement of those rights. The solution to plagiarism therefore falls most often under two categories: ethical and legal. On the ethical side, education and intercultural studies have addressed plagiarism critically, not only as a means to improve academic ethics policies (PlagiarismAdvice.org, 2008), but mainly to demonstrate that if anything the concept of plagiarism is far from being universal (Howard & Robillard, 2008). Even if differently, Howard (1995) and Scollon (1994, 1995) argued, and Angèlil-Carter (2000) and Pecorari (2008) later emphasised that the concept of plagiarism cannot be studied on the grounds that one definition is clearly understandable by everyone. Scollon (1994, 1995), for example, claimed that authorship attribution is particularly a problem in non-native writing in English, and so did Pecorari (2008) in her comprehensive analysis of academic plagiarism. If among higher education students plagiarism is often a problem of literacy, with prior, conflicting social discourses that may interfere with academic discourse, as Angèlil-Carter (2000) demonstrates, we then have to aver that a distinction should be made between intentional and inadvertent plagiarism: plagiarism should be prosecuted when intentional, but if it is part of the learning process and results from the plagiarist’s unfamiliarity with the text or topic it should be considered ‘positive plagiarism’ (Howard, 1995: 796) and hence not an offense. Determining the intention behind the instances of plagiarism therefore determines the nature of the disciplinary action adopted. Unfortunately, in order to demonstrate the intention to deceive and charge students with accusations of plagiarism, teachers necessarily have to position themselves as ‘plagiarism police’, although it has been argued otherwise (Robillard, 2008). Practice demonstrates that in their daily activities teachers will find themselves being required a command of investigative skills and tools that they most often lack. We thus claim that the ‘intention to deceive’ cannot inevitably be dissociated from plagiarism as a legal issue, even if Garner (2009) asserts that generally plagiarism is immoral but not illegal, and Goldstein (2003) makes the same severance. However, these claims, and the claim that only cases of copyright infringement tend to go to court, have recently been challenged, mainly by forensic linguists, who have been actively involved in cases of plagiarism. Turell (2008), for instance, demonstrated that plagiarism is often connoted with an illegal appropriation of ideas. Previously, she (Turell, 2004) had demonstrated by comparison of four translations of Shakespeare’s Julius Caesar to Spanish that the use of linguistic evidence is able to demonstrate instances of plagiarism. This challenge is also reinforced by practice in international organisations, such as the IEEE, to whom plagiarism potentially has ‘severe ethical and legal consequences’ (IEEE, 2006: 57). What plagiarism definitions used by publishers and organisations have in common – and which the academia usually lacks – is their focus on the legal nature. We speculate that this is due to the relation they intentionally establish with copyright laws, whereas in education the focus tends to shift from the legal to the ethical aspects. However, the number of plagiarism cases taken to court is very small, and jurisprudence is still being developed on the topic. In countries within the Civil Law tradition, Turell (2008) claims, (forensic) linguists are seldom called upon as expert witnesses in cases of plagiarism, either because plagiarists are rarely taken to court or because there is little tradition of accepting linguistic evidence. In spite of the investigative and evidential potential of forensic linguistics to demonstrate the plagiarist’s intention or otherwise, this potential is restricted by the ability to identify a text as being suspect of plagiarism. In an era with such a massive textual production, ‘policing’ plagiarism thus becomes an extraordinarily difficult task without the assistance of plagiarism detection systems. Although plagiarism detection has attracted the attention of computer engineers and software developers for years, a lot of research is still needed. Given the investigative nature of academic plagiarism, plagiarism detection has of necessity to consider not only concepts of education and computational linguistics, but also forensic linguistics. Especially, if intended to counter claims of being a ‘simplistic response’ (Robillard & Howard, 2008). In this paper, we use a corpus of essays written by university students who were accused of plagiarism, to demonstrate that a forensic linguistic analysis of improper paraphrasing in suspect texts has the potential to identify and provide evidence of intention. A linguistic analysis of the corpus texts shows that the plagiarist acts on the paradigmatic axis to replace relevant lexical items with a related word from the same semantic field, i.e. a synonym, a subordinate, a superordinate, etc. In other words, relevant lexical items were replaced with related, but not identical, ones. Additionally, the analysis demonstrates that the word order is often changed intentionally to disguise the borrowing. On the other hand, the linguistic analysis of linking and explanatory verbs (i.e. referencing verbs) and prepositions shows that these have the potential to discriminate instances of ‘patchwriting’ and instances of plagiarism. This research demonstrates that the referencing verbs are borrowed from the original in an attempt to construct the new text cohesively when the plagiarism is inadvertent, and that the plagiarist has made an effort to prevent the reader from identifying the text as plagiarism, when it is intentional. In some of these cases, the referencing elements prove being able to identify direct quotations and thus ‘betray’ and denounce plagiarism. Finally, we demonstrate that a forensic linguistic analysis of these verbs is critical to allow detection software to identify them as proper paraphrasing and not – mistakenly and simplistically – as plagiarism.

From words to action:visibility of management in supporting interdisciplinary team working in an acute rehabilitative geriatric hospital

Purpose: The following case study aims to explore management's, health professionals' and patients' experiences on the extent to which there is visibility of management support in achieving effective interdisciplinary team working, which is explicitly declared in the mission statement of a 60-bed acute rehabilitative geriatric hospital in Malta. Design/methodology/approach: A total of 21 semi-structured interviews were conducted with the above-mentioned key stakeholders. Findings: Three main distinct yet interdependent themes emerged as a result of thematic analysis: "managing a team-friendly hospital", "interdisciplinary team components", and "interdisciplinary team processes". The findings show that visibility of management support and its alignment with the process and content levels of interdisciplinary teamwork are key to integrated care for acute rehabilitative geriatric patients. Research limitations/implications: The emerging phenomena may not be reproducible in a different context; although many of the emerging themes could be comfortably matched with the existing literature. Practical implications: The implications are geared towards raising the consciousness and conscientiousness of good practice in interdisciplinary teamwork in hospitals, as well as in emphasizing organizational and management support as crucial factors for team-based organizations. Social implications: Interdisciplinary teamwork in acute rehabilitative geriatrics provides optimal quality and integrated health care delivery with the aim that the older persons are successfully discharged back to the community. Originality/value: The authors draw on solid theoretical frameworks - the complexity theory, team effectiveness model and the social identity theory - to support their major finding, namely the alignment of organizational and management support with intra-team factors at the process and content level. © Emerald Group Publishing Limited.

Extracting significant words from corpora for ontology extraction

We show a new method for term extraction from a domain relevant corpus using natural language processing for the purposes of semi-automatic ontology learning. Literature shows that topical words occur in bursts. We find that the ranking of extracted terms is insensitive to the choice of population model, but calculating frequencies relative to the burst size rather than the document length in words yields significantly different results.

A comparison of pseudo-paper and paper prototyping methods for mobile evaluations

The research presented in this paper is part of an ongoing investigation into how best to support meaningful lab-based usability evaluations of mobile technologies. In particular, we report on a comparative study of (a) a standard paper prototype of a mobile application used to perform an early-phase seated (static) usability evaluation, and (b) a pseudo-paper prototype created from the paper prototype used to perform an early-phase,contextually-relevant, mobile usability evaluation. We draw some initial conclusions regarding whether it is worth the added effort of conducting a usability evaluation of a pseudo-paper prototype in a contextually-relevant setting during early-phase user interface development.

Words and intelligence II:essays in honor of Yorick Wilks

Yorick Wilks is a central figure in the fields of Natural Language Processing and Artificial Intelligence. His influence has extends to many areas of these fields and includes contributions to Machine Translation, word sense disambiguation, dialogue modeling and Information Extraction.This book celebrates the work of Yorick Wilks from the perspective of his peers. It consists of original chapters each of which analyses an aspect of his work and links it to current thinking in that area. His work has spanned over four decades but is shown to be pertinent to recent developments in language processing such as the Semantic Web.This volume forms a two-part set together with Words and Intelligence I, Selected Works by Yorick Wilks, by the same editors.

Language as chunks, not words

Many people think of language as words. Words are small, convenient units, especially in written English, where they are separated by spaces. Dictionaries seem to reinforce this idea, because entries are arranged as a list of alphabetically-ordered words. Traditionally, linguists and teachers focused on grammar and treated words as self-contained units of meaning, which fill the available grammatical slots in a sentence. More recently, attention has shifted from grammar to lexis, and from words to chunks. Dictionary headwords are convenient points of access for the user, but modern dictionary entries usually deal with chunks, because meanings often do not arise from individual words, but from the chunks in which the words occur. Corpus research confirms that native speakers of a language actually work with larger “chunks” of language. This paper will show that teachers and learners will benefit from treating language as chunks rather than words.

Continuity of Pseudo-differential Operators on Bessel And Besov Spaces

We study the continuity of pseudo-differential operators on Bessel potential spaces Hs|p (Rn ), and on the corresponding Besov spaces B^(s,q)p (R ^n). The modulus of continuity ω we use is assumed to satisfy j≥0, ∑ [ω(2−j )Ω(2j )]2 < ∞ where Ω is a suitable positive function.

Identification of DNA-binding proteins by incorporating evolutionary information into pseudo amino acid composition via the top-n-gram approach

DNA-binding proteins are crucial for various cellular processes and hence have become an important target for both basic research and drug development. With the avalanche of protein sequences generated in the postgenomic age, it is highly desired to establish an automated method for rapidly and accurately identifying DNA-binding proteins based on their sequence information alone. Owing to the fact that all biological species have developed beginning from a very limited number of ancestral species, it is important to take into account the evolutionary information in developing such a high-throughput tool. In view of this, a new predictor was proposed by incorporating the evolutionary information into the general form of pseudo amino acid composition via the top-n-gram approach. It was observed by comparing the new predictor with the existing methods via both jackknife test and independent data-set test that the new predictor outperformed its counterparts. It is anticipated that the new predictor may become a useful vehicle for identifying DNA-binding proteins. It has not escaped our notice that the novel approach to extract evolutionary information into the formulation of statistical samples can be used to identify many other protein attributes as well.

Fractional Derivatives and Fractional Powers as Tools in Understanding Wentzell Boundary Value Problems for Pseudo-Differential Operators Generating Markov Processes

Mathematics Subject Classification: 26A33, 31C25, 35S99, 47D07.