If we let w id = w i(d), denote the topic proportion of topic i in dth document, for d ∈ D, then the normalized weights w ˜ i are simply computed as: (1) w ˜ i = ∑ d = 1 | D | w i d ∑ i = 1 n ∑ d = 1 | D | w i d The normalize function in line (2) of the Scoring Function is computed using Eq. (1).
In the absence of topical asymmetries, one would expect to observe only minor differences in the proportions of topics for men and women.
In the end, images are characterized by the proportion of latent topics and this representation is found to be more reliable than the BoVW-based feature while calculating the similarity between images.
Coding the transcripts with the initial framework was complicated by the fact that this framework covered only a small proportion of the topics of assessment programmes that were discussed, and by the interrelatedness of the different elements, which had initially been conceived of as discrete.
Figure 3 shows the ordered proportion of the 20 topics for the TRSAwardeeSet and Figure 4 shows the word clouds of the top 20 words for each topic.
Figure 2 illustrates the proportion of schools that rated topics as at least moderately important and moderately covered.
Data was extracted for this question, if at least two categories were analysed in a study.> whether and how the extent of information needs was evaluated, i.e. with regard to medical information in general or about specific topics (e.g. ratings of predefined topics or proportion of people who claim to have unmet information needs).
> 4. whether and how the extent of information needs was evaluated, i.e. with regard to medical information in general or about specific topics (e.g. ratings of predefined topics or proportion of people who claim to have unmet information needs).
The threshold of 0.02 was chosen, because the average number of words per analysed abstract after removal of stop-words was approximately 100 - a topic proportion of 0.02 thus corresponds to two words, which we propose is the absolute minimum for a semantic interpretation of a topic assignment.
The proportion of calls received by topic of call and type of caller did not change in any meaningful way during this time (data not shown).
