Sentence examples for refined topics from inspiring English sources

It can be argued that the choice of T is ultimately an arbitrary one driven by the research questions and the intended use of the resulting topic model; small topic numbers will result in semantically broad topics, with increasing topic numbers, those broader topics will be split in semantically more refined topics.

After each interview, the research assistant will complete a summary interview report in which he will note any recommendations for future interviews (questions to be refined, topics to be added, etc).. Also, after each interview, the research assistant and one of the investigators (Loignon) will review and discuss the interview.

Emergent themes were reviewed by HL-Q and thematic analysis of initial interviews was used to inform and refine topics for discussion in subsequent interviews.

To better understand how non-expert users understand, assess, and refine topics, we conducted two user studies an in-person interview study and an online crowdsourced study.

Our results suggest that the methodology for query modification conditioned to query verbosity detection and topic gisting is significantly effective and that query modification should be refined when topic difficulty and query verbosity are considered since these two properties interact and query verbosity is not straightforwardly related to query length.

We developed a preliminary list of suggested topics and stakeholders refined and ranked topics based on their importance.

Stakeholders revised our preliminary list of CER topics by refining the proposed topics and adding additional topics.

Backpropagation allows us to slightly perturb and refine these topics with respect to the output labels, thereby, facilitating learning of features that are optimal for discriminative tasks.

Second, identifying issues would benefit from face-to-face question generation where facilitators could help refine emerging topics into PICO-structured research questions.

Guideline development can be divided in six phases: prioritizing topics, refining the subject area, assembling development groups, identifying and assessing evidence, translating evidence into clinical practice guidelines and finally reviewing and updating guidelines [ 12].

In particular, our findings include: (1) analysis of how non-expert users perceive topic models; (2) characterization of primary refinement operations expected by non-expert users and ordered by relative preference; (3) further evidence of the benefits of supporting users in directly refining a topic model; (4) design implications for future human-in-the-loop topic modeling interfaces.