we present snowy a visualization system that recommends utterances
for conversational visual analysis to guide users throughout their analysis
snowy recommends utterances at different points including at the start of a session
as follow-ups for user utterances
as well as deictic utterances that complement direct manipulation actions such as selections
to generate recommendations snowy monitors a user's interactions to track which fields have
been looked at as well as what types of analytical intents the user is interested in combining this
information with the active interface state snowy shortlists the types of recommendations
it should present parameterizing them so that they promote data and analytical coverage
and generates phrasings that showcase the linguistic variability supported by the tool
a preliminary user study with 10 participants suggested that snowy's recommendations support
conversational visual analysis by guiding the participants analytical workflows and promoting
the use of natural language as an example of how utterance recommendations can aid visual analysis
let's consider a usage scenario tintin an analyst at a production house is using snowy
to explore a data set of movies to understand what type of movies his company should invest in
to help tintin kick-start his exploration snowy automatically processes the data
to identify interesting patterns and presents these as utterances to tintin
finding the recommendation about looking at worldwide grows over time
to be interesting tintin selects it as its input utterance snowy now updates the recommendations
to include follow-up utterances to drill down into the current chart
curious about the trend across different content ratings tintin selects compare across
content ratings as his next utterance and notices that pg-13 has the most stable trend
skimming through the updated recommendations tintin notices that snowy is suggesting that
tintin looks at production budget instead of worldwide gross through the recommendations
phrasings tintin also learns that he can use natural language to swap and compare attributes
as tintin again looks at the recommendations to see what he should ask next he sees that he can
ask snowy to compute averages across groups of genres curious to see other potential
group-based queries tintin requests similar recommendations and subsequently selects an
utterance to compare the gross values across movie genres inspecting the chart tintin notices that
action and adventure have much higher values compared to other groups snowy also makes this
observation and suggests an utterance for tintin to drill down into the highest grossing genre
analyzing tintin's actions so far to ensure that he gets a broad perspective of the data
snowy now suggests that tintin should look at other fields such as the movie ratings
realizing that he has not considered movie ratings tintin selects the recommended utterance as
his input remembering that tintin had grouped data by content ratings while looking for trends
snowy now suggests applying a filter to focus on pg-13 movies
since this was a group of movies he was interested in earlier tintin uses the suggested utterance and
confirms that the ratings from different platforms are fairly correlated next tintin wants to resume
his investigation of the return on investment by comparing growth and budget since he knows which
fields he wants to look at he uses the manual view specification panel to update the current chart
snowy clears the natural language input box since the previous utterance is no longer active but
still updates its recommendations in case tintin wants to issue new natural language utterances
through the follow-up recommendations tintin realizes he has not considered the creative
types and selects an utterance to see the types of movies as part of the active chart
finally to inspect movies with a high gross and return on investment
tintin selects points on the chart as he makes a selection snowy suggests utterances he could
use to perform calculations on his selected points tintin issues the utterance to compute
average values and notes the potential return on investment for pg-13 movies
that belong to specific genres and creative types to share with his financial team