How good are ideas identified by an automatic idea detection system?

Online communities can be an attractive source of ideas for product and process innovations. However, innovative user‐contributed ideas may be few. From a perspective of harnessing “big data” for inbound open innovation, the detection of good ideas in online communities is a problem of detecting rare events. Recent advances in text analytics and machine learning have made it possible to screen vast amounts of online information and automatically detect user‐contributed ideas. However, it is still uncertain whether the ideas identified by such systems will also be regarded as sufficiently novel, feasible and valuable by firms who might decide to develop them further. A validation study is reported in which 200 posts from an online home brewing community were extracted by an automatic idea detection system. Two professionals from a brewing company evaluated the posts in terms of idea content, idea novelty, idea feasibility and idea value. The results suggest that the automatic idea detection system is sufficiently valid to be deployed for the harvesting and initial screening of ideas, and that the profile of the identified ideas (in terms of novelty, feasibility and value) follows the same pattern identified in studies of user ideation in general.     

How good are clinical MEDLINE searches? A comparative study of clinical end-user and librarian searches

The objective of this study was to determine the quality of MEDLINE searches done by physicians, physician trainees, and expert searchers (clinicians and librarians). Its design was an analytic survey with independent replication in a setting of self-service online searching from medical wards, an intensive care unit, a coronary care unit, an emergency room, and an ambulatory clinic in a 300-bed teaching hospital. Participating were all M.D. clinical clerks, house, and attending staff responsible for patients in the above settings. Intervention for all participants consisted of a 2-h small group class and 1-h practice session on MEDLINE searching (GRATEFUL MED) before free access to MEDLINE. Search questions from 104 randomly selected novice searches were given to 1 of 13 clinicians with prior search experience and 1 of 3 librarians to run independent searches (triplicated searches). Measurements and main results from these unique citations of the triplicated searches were sent to expert clinicians to rate for relevance (7-point scale). Recall (number of relevant citations retrieved from an individual search divided by the total number of relevant citations from all searches on the same topic) and precision (proportion of relevant citations retrieved in each search) were calculated. Librarians were significantly better than novices for both. Librarians had equivalent recall to, and better precision than, experienced end-users. Unexpectedly, only 20% of relevant citations were retrieved by more than one search of the set of three, with the conclusion that novice searchers on MEDLINE via GRATEFUL MED after brief training have relatively low recall and precision. Recall improves with experience but precision remains suboptimal. Further research is needed to determine the "learning curve," evaluate training interventions, and explore the non-overlapping retrieval of relevant citations by different searchers.     

How healthy are software engineering conferences?

In this article we study the health of software engineering conferences by means of a suite of metrics created for this purpose. The metrics measure stability of the community, openness to new authors, introversion, representativeness of the PC with respect to the authors' community, availability of PC candidates, and scientific prestige. Using this metrics suite, we assess the health of 11 software engineering conferences over a period of more than 10 years. In general, our findings suggest that software engineering conferences are healthy, but we observe important differences between conferences with a wide scope and those with a more narrow scope. We also find that depending on the chosen health metric, some conferences perform better than others. This knowledge may be used by prospective authors to decide in which conferences to publish, and by conference steering committees or PC chairs to assess their selection process.     

How close are we to understanding v1?

A wide variety of papers have reviewed what is known about the function of primary visual cortex. In this review, rather than stating what is known, we attempt to estimate how much is still unknown about V1 function. In particular, we identify five problems with the current view of V1 that stem largely from experimental and theoretical biases, in addition to the contributions of nonlinearities in the cortex that are not well understood. Our purpose is to open the door to new theories, a number of which we describe, along with some proposals for testing them.     

How to construct small probabilistic roadmaps with a good coverage?

We investigate how we can construct small probabilistic roadmaps in a reasonable time while still keeping a good coverage and connectivity. We propose a new neighborhood-based method that can reduce the size of the roadmaps by filtering out unnecessary nodes. We then experimentally test it against a basic probabilistic roadmap planner and a visibility-based planner. We use both a uniform sampling and a bridge test sampling in our tests. The results show that the neighborhood-based method can reduce the number of nodes considerably. The neighborhood-based method is simple to implement, it works well with a uniform sampling, and it does not need any additional parameters when compared with the basic planner.     

How useful are strategic plans for information systems?

Although much research has been done in the area of strategic planning for information systems (IS), relatively less research has focused on the output of the IS planning process, namely, the IS plan. This paper examines the usefulness of IS plans through a field survey of 136 IS executives. Results indicate that IS plans are generally perceived to be useful for supporting business objectives, improving systems integration, exploiting information technology (IT) for competitive advantage, and prioritising IS development projects. Conversely, IS plans are perceived to be less useful for clarifying the role of IS, evaluating IS performance, anticipating surprises and crisis, and adapting to unanticipated situations. Implications of these results are discussed.     

Explicit versus implicit models: What are good languages for modeling?

Software and Systems Modeling -