The Mobile Web promises a new age of anytime, anywhere information access to billions of users across the globe. However, the Mobile Internet represents a challenging information access environment, particularly from a search standpoint. In this paper we present two visual interfaces for improved mobile search. First, we present SearchBrowser, a map-based interface that offers richer end-user interactions by taking into account important mobile contexts including location and time. Second, we consider the social context of mobile search and present SocialSearchBrowser; a proofof-concept interface that incorporates social networking capabilities to improve the search and information discovery experience of mobile subscribers.
The early work presented in this paper was carried out while Karen Church was a PhD student in University College Dublin. This material is based on works supported by the Science Foundation Ireland under Grant No. 03/IN.3/I361 and Grant No. 07/CE/I1147. The later work, i.e. the SocialSearchBrowser prototype is being carried out at present in Telefonica Research. yCLARITY: Centre for Sensor Web Technologies. 1http://www.un.org/apps/news/story.asp?NewsID=28251 &Cr=Telecommunication&Cr1
However, the Mobile Internet represents a challenging information access environment, particularly from a search standpoint. Limited screen-space and restricted text-input and interaction capabilities exacerbate the shortcomings of modern Web search. To date most mobile search interfaces are simple adaptations of standard Web interfaces, where users are presented with a ranked list of results. For mobile search to succeed we need to think beyond simply query-based interfaces and towards interfaces that can offer richer interactions by taking into account important mobile contexts that have an impact on mobile users needs.
In this paper we focus on the mobile search interface and
we offer on a more radical rethink of mobile search. It has
always been our contention that mobile search differs
significantly from Web search, not just because of the devices but
also because people’s information needs differ when mobile.
Previously we examined the information access patterns of
real mobile subscribers using log analysis techniques [
Based on the findings of these previous studies, we devised two new visual interfaces for mobile search, both designed to emphasise the importance of location, time and preferences as key elements of search context. Unlike traditional search interfaces, which require user input before providing information to end-users, our interfaces give mobile users interesting information from the beginning. Our approach is designed to change the mobile search paradigm. The interfaces present historical query, comment and result-selection data for users to navigate through on an interactive map-based interface. The rich user interface enables users to interact with the past activities of other users, execute searches, view past result-selections and filter queries based on context information. In short by presenting users with information about what others are searching for we believe we can offer an improved search experience.
This paper is organized as follows. In the following section
we present some related work. Next, we describe
SearchBrowser, a map-based interface that offers richer end-user
interactions by taking into account important mobile
contexts including location and time and we describe the results
from a recent user study. Based on the outcomes of this
evaluation and the findings from our diary study [
More recently researchers are investigating the social side to
Web search. For example, Collaborative Web Search (CWS)
involves utilising the search histories (i.e. queries and
resultselections) of communities of like-minded individuals. In
[
Another approach is to exploit Web 2.0 technologies,
specifically Web annotations, to improve Web search. The basic
premise is that by allowing users to annotate search results
and to share these annotations with others, the search
experience can be improved. In [
Another related area of interest is social search. Social search in this context involves exploiting different forms of human judgements, ratings and interactions to improve the overall search experience. For example, Microsoft’s U Rank2, is a prototype search engine that allows people to edit, annotate and organise search results. U Rank enables users to collaborate with one another through sharing and recommendation of search results in easily accessible lists.
Most relevant to our current work is utilizing social
networks to enhance search results and online interactions. In
[
Our Proposal & Contributions Our current work is similar in nature to the QnA approach. The QnA system essentially tags queries with a location. These queries are displayed on a map-based interface enabling users to visualise the search space. The QnA prototype does not, however, provide any means for a user to filter queries, other than by location. Given that the volume of queries at specific locations is likely to be quite high and there is no means to filter queries, the QnA prototype raises a new interface/presentation challenge. Furthermore, our prototypes focus on the social side to mobile search allowing users to interact with the result-selections and comments of other users. In the SocialSearchBrowsr application, we investigate this social context further by utilizing social 2http://research.microsoft.com/projects/urank/ networks for improved information access. We think this is a core area to address given the unique characteristics of the mobile space. Thus the core contributions of this paper are as follows: (1) we present SearchBrowser, a contextaware mobile search interface that enables situated discovery of information, (2) we describe a recent user evaluation of SearchBrowser and demonstrate some initial positive results and (3) we propose SocialSearchBrowser, an extension of SearchBrowser, which explores the social context of search by incorporating social networking to improve the information access experience of the end-user.
THE SEARCHBROWSER INTERFACE The basic premise behind the SearchBrowser interface is that by allowing users to see what other users have been searching for and interacting with, we can improve the search experience. The interface utilises contextual information such as location and time to provide a unique experience. The interface provides mobile users with information more proactively, thus encouraging discovery of content. The prototype3 consists of a text box that allows users to issue new queries and a small map centered at the user’s current physical location. The map shows queries submitted by other users in that location and two sliders at the bottom of interface are used to filter the queries displayed on the map. The Map Interface When the user first initialises the application, he/she is shown a map centered at their current location (Figure 1). The map shows all recent queries entered by other users in that location. We refer to these queries as the prime set. The map is updated periodically so that newly entered queries are displayed. Queries submitted by other users, but without any result selections, are identified by a small magnifying glass with an associated label (See Figure 1 icon (1)), while queries that have resulted in the selection of at least one Web search result are identified by the small globe/Web icon with an associated label (See Figure 1 icon (2)). The label displays the actual query text. If a query or result-selection has a comment associated with it, the associated icon is augmented with a small user image. Comments can come in the form of answers, suggestions, tags, descriptions, general comments/remarks, etc. Queries with comments are shown in Figure 1 icons (3) and (4).
Search Histories
Clicking on the query icons/labels opens an information
window/bubble (Figure 2), showing the query, the time the query
was last executed and a link to execute the query in
question. If the query lead to a result-selection the information
window also displays the most recent result-selections.
Furthermore, if the query has any comments associated with it,
a link to view these comments is also shown (Figure 3
illustrates the comments facility). Users can choose to go directly
3The work presented in this paper builds upon earlier work
presented in [
1. Query 3. Query with comments
SearchBrowser interface on startup to one of the listed URLs or to re-execute the query4. To help users distinguish between popular queries, the icon sizes of the queries change based on their popularity. We use a simple measure of popularity based on the number of times the query has been submitted and the amount of resultselections and comments associated with the query. Smaller icons indicate a low level of interactivity, while larger icons indicate a high level of interactivity.
Context Sliders At the bottom of the interface there are two sliders. One slider represents time while the other slider represents query similarity. Users can manipulate the sliders to adjust the set of prime queries and to filter these queries. For example, users can adjust the time slider to go back in time and display queries submitted during different time periods. Thus rather than simply displaying queries submitted now (i.e. in the last couple of hours), users can view queries submitted over the entire day, yesterday, the last few days, last week, etc. The same principle applies to the query similarity slider. However, instead of time, the query similarity slider filters by query term overlap. When a user accesses the application, the system automatically calculates the similarity between the user’s queries and all other queries in the dataset. Moving the query similar slider, changes the similarity threshold and thus filters queries from the prime set. In the following section we describe our evaluation of SearchBrowser. 4Note that if a user chooses to re-execute a query they will receive a set of results from the standard Google search engine.
EVALUATING SEARCHBROWSER We had two main aims in carrying out an evaluation of the SearchBrowser interface. First, we wanted to assess the effectiveness of the interface, focusing on key features of the interface and their usefulness. Second, we wanted take the first steps to investigate the potential of the new interface to encourage discovery of new interesting content.
Dataset To demonstrate the range of functionalities supported in the SearchBrowser application, we needed a source of queries, comments and result-selections as the basis of our dataset. To generate the seed queries, we manually extracted > 200 entries from the online WikiMapia service, focusing on entries with a latitude/longitude in the central Dublin, Ireland. WikiMapia5 is a Web 2.0 application designed to encourage users to describe the world. WikiMapia allows users to mark areas on a Google map and describe those areas using titles, descriptions, tags, categories, images and links to external URLs. Given that each entry in WikiMapia includes rich descriptive information, along with an original creation date and a physical latitude/longitude value, it provided a good basis to generate seed user queries for our evaluation. To generate realistic queries we then asked 3 different users to view the list of WikiMapia entries and to formulate a query for each6. This resulted in 444 generated queries which were then used as a basis for the prime dataset7. For each query, we extracted the associated WikiMapia entry, generated a random date and latitude/longitude within the chosen time period and given location boundary, i.e. central Dublin)8. Any URLs associated with the WikiMapia entry were used as the result-selection(s) and if the entry had tags associated with it, we used the corresponding title/name as the comment. The outcome was a set of time-stamped, geocoded, query, comment and result-selection data.
Participants & Methodology 20 participants took part in the study, 18 male and 2 female. The participants comprised a mix of computer science staff and post-graduate students from UCD, ranging in age between 25 and 40 (average: 30, standard deviation: 4.23). 85% of users had some previous Mobile Internet experience, but most of these users (approximately 60%) accessed the Mobile Internet on an infrequent basis.
The participants carried out the experiment online using a standard Web browser. The Web browser emulated the SearchBrowser interface by using similar screen real-estate to an iPhone (320 x 480 pixels). Participants were asked to (1) to familiarise themselves with the interface for the first few minutes of the experiment and (2) to formulate and submit five queries of their own using the interface. We informed participants that the queries were open-ended, however, we did ask participants to bear in mind that the interface is designed for mobile devices and as such would be used while on-the-go. When generating their queries, we asked participants to try to think of things they might need/like to find out if mobile and in the location presented on the map. Before they were exposed to the interface the participants were presented with a description of the various features of the interface. At the end of the evaluation, users were presented with a post-task questionnaire designed to measure their subjective reactions to the interface9.
Usage Results 6Each participant was presented with the same list of WikiMapia entries and participants were instructed to generate queries for as many entries as possible out of the list of > 200 entries. 7We are aware that artificially generating queries in this manner is a limitation of this study. However, without deploying SearchBrowser, it is impossible to obtain a realistic source of queries. For users to evaluate the application we needed to be able to show them a sample of queries, comments and result-selections and WikiMapia offers a rich set of geo-coded data as the basis. 8A note on random location values: in a realistic setting it is unlikely that a user will always submit a query related to an exact physical location. For example, if the user wants to know where they can find a coffee shop on a particular street, the query could be generated anywhere along that street or within close vicinity to that street. Therefore, we opted to generate a random latitude/longitude within close vicinity to the actual latitude/longitude value. 9This study allowed us to gather interesting feedback about the interface and it’s overall usability. We are aware that the evaluation is limited in that is does not take place in a mobile setting, however, we feel that the evaluation in it’s current form still yields some interesting results and represents an important first step in our ongoing work in the mobile search space.
In this section we focus on the quantitative results by exploring the user interactions with the map-based interface as well as general usage statistics.
Interactions with the Map Interface Using click-thru and mouse-over data we were able to analyse what features of the map and user interface the participants interacted with. Although the level and type of interaction with the SearchBrowser interface is likely to be different in a real mobile setting, we were still interested in examining interactions with the map so that we could gather some insights into which features of the current user interface participants were drawn too. Overall we found a high degree of interactivity from end users. All users interacted with the map based interface using both zoom and drag functions to navigate. All users clicked on either a query or result selection marker and opened an information window bubble. We found that 95% of users clicked on the query markers while 75% of users clicked on the result-selection markers. We also found a high degree of interactivity with the various markers/query icons, with mouseover events tracked for the vast majority of users. Thus, users did interact with the queries and past result-selections of other users.
We found that most users selected search results within the SearchBrowser application. However, only 10% of users chose to click on a URL in the result-selection bubbles, thus indicating a low level of interactivity with the past resultselections of other users. Our later analyses indicate that poor search results may have been the main cause for such a low level of interaction. We also found that 70% of users chose to view the comments of other users, but less than 50% chose to generate comments of their own10.
Search Usage
The results so far demonstrate that from an interactivity
standpoint, all users engaged with the SearchBrowser interface.
Table 1 presents some basic usage statistics. The participants
generated almost 300 queries, 126 of which were newly
generated queries (i.e. submitted via the search box and not
through interactions with queries presented on the map
interface). Interestingly we find that 45% of all newly submitted
queries by participants lead to at least one result-selection.
This represents a significant increase on the success rates
found in [
Questionnaire Results In this section we examine the participants’ subjective reactions to SearchBrowser. At the end of the evaluation, users were presented with a post-evaluation survey. The survey was designed using a combination of questions from wellestablished usability questionnaires such as QUIS11 and the 10In most social websites, the majority of users don’t actively participate in the generation of new content. In an analysis from Yahoo! Groups, 1% of users actively create new content, 10% of users actively contribute to such content (e.g. replying to a blog post) while 100% of users benefit by reading/viewing the content generated by the others. See http://www.elatable.com/blog/?p=5. 11Questionnaire for User Interface Satisfaction: http://hcibib.org/perlman/question.cgi?form=QUIS
Total Mean (per-user) Min Max SD # Users % Users
IBM Computer Usability Satisfaction Questionnaires12. We also included some more detailed usability and user-acceptance questions focusing on key aspects of the SearchBrowser interface. Participants rated their agreement with various statements on a 7-point anchored likert scale13, with a rating of 1 indicating “strongly disagree”, a rating of 7 indicating “strongly agree”, while a rating of 4 indicates “neutral”. The survey questions fell into three categories: (1) overall satisfaction, (2) application features and (3) user interface (UI). A full list of questions can be found in the appendix. Overall Satisfaction
Q M1 SD
M2
M3 1 2 3 4 5 6 7 8 4.50 5.85 5.55 5.85 3.70 4.00 5.65 5.30 1.47 1.35 1.28 1.14 1.66 2.00 1.27 1.42 5 6 6 6 4 4 6 5 5 7 5 7 4 4 6 5 1 1 0 0 0 1 2 0 0
Frequency Count 2 3 4 5 6 0 5 2 7 4 1 0 2 3 6 1 0 2 6 6 0 0 3 5 4 5 3 6 1 3 3 4 4 2 1 1 0 2 4 8 1 0 5 6 2 7 1 8 5 8 1 4 5 6
The list of satisfaction questions can be found in Table 7 in the Appendix. Overall, the participants’ subjective assessment of satisfaction with the application was positive, with an average response of 5.05. Participants found the application easy to use (q2=5.85) and easy to learn (q4=5.85). They found performing tasks to be straightforward (q7=5.65) and in general felt that they could imagine using the application while mobile (q8=5.3). However, users were unbiased in their rating of statement 6 regarding expected functions and capabilities, and we found the general satisfaction rating assigned by users was more neutral (q1=4.5). We attribute this to one key issue: users found it somewhat difficult to find the information they needed/wanted (q5=3.7). The goal of this evaluation was not to assess the search result quality, but rather the interfaces effectiveness and in this evaluation we were limited by the underlying search engine. We used the Google search API for the search component of the application. We attempted to localise the queries by appending the 12http://drjim.0catch.com/usabqtr.pdf 13http://en.wikipedia.org/wiki/Likert scale Q
SD terms Dublin and Ireland to participant queries before issuing them to Google. However, one of the main comments by participants was that the search results were not as localised as they expected/wanted.
Application Features
M2
M3
The list of feature questions can be found in Table 5 in the Appendix. We found the majority of users were almost unbiased in their responses to the first set of questions regarding the query feature. For example, we found that in general participants didn’t find that they interacted with queries frequently (q5=3.55) and they were unsure as to whether other people’s queries helped them form their own queries (q6=4.2). However, users did rate statements 7, 8 and 9 positively, indicating that the queries provided an understanding of the type of information that is relevant to the location. Users liked the ability to browse other user queries. Furthermore, they thought it was an interesting way to discover new information (q8=5.85) and it helped them learn about other people in the area (q9=5.4). One of the main aims of the evaluation was to assess whether users liked the exploratory interface provided by SearchBrowser and these initial results indicate that this may be the case.
Although participants found the ability to view result-selections useful (q11=5.60), they found they did not interact frequently with the result-selections of others (q11=3.8) and were neutral in their opinion as to whether the result-selections of other users provided them with additional information about the query (q12=4.45). We attribute this finding to the poor quality of the search results presented to users. It is likely that the ratings for such features would increase if the search results returned improved.
The comments feature resulted in a relatively neutral rating on average (q14=3.95, q15=4.10). In fact we find that participants were quite divided in their opinion on the usefulness of the comments feature. For example, when asked if the comments feature helped them to learn more about the query, we find that 10 users agreed, 3 users were unbiased and a further 7 users disagreed (q15). Interestingly we found that users were more in agreement that they added comments to their own queries (q19=3.45), rather than adding comments to other people’s queries (q18=1.55). After examining the remarks of participants about the comments feature, we found that some users were not clear on what constitutes a comment. This is something we look at improving in the SocialSearchBrowser application.
User ratings for the two slider features were generally positive. We found that 12 users (60%) assigned a positive rating when asked if the time slider is useful, while 13 of the users (65%) liked being able to filter queries based on time. Users found the time slider more intuitive and as such interacted with the time slider more frequently. Reaction to the query similarity slider was less positive overall. For example, users were quite neutral when asked if the query similarity slider was useful (q23=4.15), however they were quite positive when asked if they liked being able to filter queries based on query similarity (q25=5.05). Interestingly, we find that when we examine the frequency count for each of the 7 ratings assigned to the slider questions, the most popular rating is strongly agree (score of 7), indicating that the users who did like the slider features found them very useful. Overall the SearchBrowser features were well-received by participants, with the queries and time slider features rated most positively out of the five feature sets. The results indicate that with some straightforward improvements, the remaining features (result-selections, comments and query similarity slider) could become more effective.
User Interface The list of user interface questions can be found in Table 6 in the Appendix. Most of the participants were satisfied with the interface (q1=5.05), found the interface pleasant (q2=5.9), intuitive (q17=5.9) and liked interacting with the interface (q3=5.75). Users also found the interface easy to interact with (q14=6.2). Furthermore, users were able to easily explore the various features of the map (q16=5.9) indicating that perhaps such an interface would work well as a information discovery tool in the mobile space. Users noticed the queries on the map (q4=6.45), enjoyed the icons used to represent queries (q5=5.45) and were somewhat positive as to the intuitiveness of the query icons (q6=4.85).
When examining the two sliders, we find that users rated the time slider more highly, indicating that they noticed the time slider (q7=6.45), they found it intuitive (q8=6.3) and they liked the time slider (q9=6.3). The ratings assigned to similar statements for the query similarity slider, although positive, leaned more towards an unbiased rating. As mentioned in previous sections, we included the time and query similarity sliders in the SearchBrowser application so that users could quickly and easily filter the set of queries displayed on the map. However, even with such features, we find at times that the interface became cluttered with information (q15=4.4) thus making it more difficult to read the information presented (q13=4.95).
Overall we found the response to the user interface by participants was very positive, with the majority of users assigning top marks to the vast majority of statements, thus indicating that the current SearchBrowser interface design is both usable and aesthetically pleasing.
Q
SD
As well as asking users to rate their perceptions of the SearchBrowser application on the 7-point likert scale, we also asked users some more general freeform questions. 90% of users said they would use the SearchBrowser application if the service was easily/readily available. When asked under what circumstances would they use such an application, participants submitted a range of responses including, if there were in an unknown physical place (e.g. a new city), to find information about local services/products, to keep up-to-date with current events and finally to find directional/travel-related information. Interestingly, users also commented on the social aspect of the application, indicating that the social side to the SearchBrowser application could be very useful for query recommendations.
Overall the results of the evaluation were positive. The
SearchBrowser study represented an important first step in
evaluating this type of interface and it provided us with some
valuable feedback regarding the interface components and the
supported interactions. However, the evaluation results also
encouraged us to re-think some elements of the prototype.
Furthermore, results from a recent diary study of mobile
information needs indicate that mobile users seek fresh content
that is location and time specific and is influenced by social
context [
SOCIALSEARCHBROWSER
Human beings, by their nature are social creatures. We live
by communicating with others, building relationships and
forming friendships. In fact, many people view the mobile
phone as a social communications device, that is, a device
which can be used to stay in contact with friends and family
[
The Facebook application comprises of an information page showing all queries submitted through the SocialSearchBrowser interface. The information page lists the query submitted, the name of the user who submitted the query, the location of the user and a timestamp indicating when the query was submitted (See Figure 5). Clicking on the query opens a more detailed information page (See Figure 6). The detailed page shows relevant query details but also displays a Google map of where the user was at the time the query was executed. It also shows a list of any answers/comments submitted for the query and a form for entering new answers/comments. In this way Facebook users can see what queries their friends have executed on the go, where and when their friends executed these queries and any answers provided to these queries. To envisage how the SocialSearchBrowser would work, imagine the following scenarios: Amy is wandering around Plaza de Catalunya in Barcelona as part of her weekend away in Spain. She wants to know where she can find a nice restaurant that serves tapas but she wants to avoid touristy places. Amy takes out her iPhone, opens the browser and connects to SocialSearchBrowser. Amy is presented with a map centered at her current location. The map displays other queries and user interactions that have taken place in her current location. Amy is able to get an idea of the types of needs that arose from other mobile users in this location. Amy doesn’t see any queries on the map related to tapas so she decides to submit her own query. Thus, Amy enters the query “good tapas” via the SocialSearchBrowser interface. Amy is presented with a localized list of Web search results for her query. At the same time a notification is sent to Amy’s facebook friends indicating that Amy is in Barcelona and that she’d like some help with a query. A few minutes later Amy is alerted that one of her friends has submitted an answer to her query. Amy returns to the map, clicks on her query and is shown the answer(s) submitted by her friend(s). Perfect, now Amy knows exactly where to go for great tapas! David is in the middle of Dublin city center, sipping on a coffee and is thinking about what to do this weekend with friends. He takes out his iPhone, opens the browser and connects to SocialSearchBrowser. David is presented with a map centered at his current physical location. David is able to see straight away that other users have entered queries like “coffee to go” and “salsa classes” in this location. David decides he wants to explore what else other people in this location have been interested in. He moves the temporal slider towards the earlier marker and the map is updated with lots of different queries entered in this location. David see’s lots of queries related to comedy events. David then uses the social filter to show only queries submitted by his friends and he notices that his friend Tony was looking for tickets to see a comedy show last week. David decides to call Tony to see if he’d like to go to a comedy show this weekend.
Ideally, when queries are submitted via SocialSearchBrowser, a user’s friends will be online and will be able to offer help immediately. This scenario could also be extended to allow anyone to answer queries, but in this case, answers generated by close friends of the user would be rated higher. Other social factors could also be explored. For example, in the current prototype we include a social slider for filtering queries so that only queries generated by friends are displayed. We could also investigate filtering friend locations, i.e the set of locations where your friends executed queries, etc. Thus, SocialSearchBrowser provides an alternative means of mobile search and information discovery, taking into account key mobile contexts such as location and time, while exploiting the social context of search. Users are encouraged to discover new, interesting content and perhaps new, interesting places. The new prototype utilizes a users social network to improve the information access experience, allowing friends to provide helpful information through realtime query answering. Furthermore the application enables a new form of social discovery by allowing friends to share queries and online interactions while mobile.
CONCLUSIONS Mobile information access is challenging, particularly from a search perspective. In this paper we described two new interfaces for improving mobile search and discovery. The first interface, SearchBrowser, presents users with historical query, comment and result-selection data on a rich mapbased. The application takes important mobile contexts into account such as location and time. Results of an initial user trial were positive and demonstrated that the current interface design is easy to use, easy to learn and aesthetically pleasing to end-users. Based on user feedback from this evaluation and results of a recent diary study of mobile information needs, we developed an extended proof-of-concept prototype, that explores the social context of mobile search. SocialSearchBrowser is an innovative interface that incorporates mobile contexts with social networking capabilities to improve the search and information discovery experience of mobile subscribers. SocialSearchBrowser allows friends to provide help to mobile users in the form of answers, comments, suggestions, links and tags, through a Facebook application. Furthermore, the interface incorporates a social filter which enables mobile users to filter the set of queries displayed to show only friend queries, helping to visualise friend queries and interactions.
We are currently investigating a number of different areas relating to the prototype. Firstly, we are in the process of implementing a fully functional working prototype which we plan to test and evaluate with real users in a live mobile field study. We have also identified a number of interesting future directions that explore the social context of search in more detail. We’d like to consider other social filtering approaches. For example, we could show popular friend queries and allow users to visualize the most common locations in which friends have had previous mobile information needs. We could also exploit social networks to provide personalized query and location recommendations. For example, a mobile user might be interested to learn about a new street in their city where a number of their friends have submitted previous mobile queries. We’re also interested in the automatic identification of ‘close friends’ vs ‘not so close friends’, based on facebook activity, presence in mobile phone contacts and other informative resources. No. 1 2 3 4 5 6 7 8 9 10 11 12 13 16
I found other people’s queries useful I found other people’s queries informative I found other people’s queries intriguing I found other people’s queries distracting I interacted with other people’s queries I found that other people’s queries helped me form my own queries Many of the queries displayed helped me to understand the sort of information that was relevant to the location being browsed The ability to browse other people’s queries is an interesting way to discover new information.
The queries helped me to learn about other people in the area, their needs and preferences The ability to view other people’s past result-selections is useful I interacted with other people’s past resultselections The result-selection feature provided me with additional information about the query The result-selection feature helped me find answers to the queries I found the comments feature useful The comments associated with a query helped me learn more about the query The comments associated with a query helped me find answers to the query I viewed other people’s comments I added comments to other people’s queries I added comments to my own queries I found the time slider useful I interacted with the time slider I liked being able to filter the queries displayed on the map based on time I found the preference slider useful I interacted with the preference slider I liked being able to filter the queries displayed on the map based on query similarity 2 3
Overall, I am satisfied with the search browser interface The interface of the search browser application was pleasant I liked using the interface of the search browser application I noticed the queries on the map I liked the query icons I found the query icons intuitive I noticed the time slider I found the time slider intuitive I liked the time slider I noticed the query similarity slider I found the query similarity slider intuitive I liked the query similarity slider I was able to easily read information on the interface It was easy to interact with the interface The organization of information on the map was clear I was able to easily explore the various map features The interface was intuitive
Overall, I am satisfied with the search browser application It was simple to use the application I felt comfortable using the application It was easy to learn to use the application It was easy to find the information I needed The application had all the functions and capabilities I expect it to have Performing tasks is straightforward I could imagine using this type of application when out and about.
Leaving cost aside, would you use the search browser application if the service was easily/readily available? What circumstances do you think you might find the search browser application useful? What did you like about the search browser application? What if anything did you find frustrating or unappealing about the search browser application? How could we make the search browser application more useful for you?