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  • 1. G.Lakshmi, K.Rajendar, J.Pratap / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.1387-1392 SparkClouds: Incorporate Spark Lines into a Tag Clouds G.Lakshmi K.Rajendar J.Pratap M.Tech(C.S.E). M.Tech(C.S.E) . M.Tech(P.hd.). VCET,Karimnaga,Ap. JITS ,Karimnagar,Ap. VCET,Karimnagar,Ap.Abstract The aim of this project is to introduce have proliferated over the web. They are now aSpark Clouds, which integrate spark lines into a common visualization in news sites for displayingtag cloud to convey trends between multiple tag the most active news story themes , photo sharingclouds. Spark Clouds ability is to show trends sites for conveying the distribution of image contentcompares favorably to the alternative , and social bookmarking sites for showing popularvisualizations. In the Existing System, Tag clouds tags . In fact, several online programs are availableare used to display the relative tag frequency, that help you create your own tag clouds frompopularity, or importance by font size. They different types of text sources .serve as a visual summary of document content.Tag clouds seem to invite exposure of their Tag clouds can evolve as the associatedevolution over time; they do not explicitly data source changes over time. For example, the USrepresent them. In the proposed System, we Presidential Speeches tag cloud shows theintroduce Spark Clouds, a new breed of tag cloud popularity, frequency, and trends in the usages ofthat incorporates spark lines with more typical words within speeches, official documents,tag cloud features to convey evidence of change declarations, and letters written by the Presidents ofacross multiple tag clouds. Spark Clouds retain the US between 1776 and 2007 ]. Other sources ofthe advantages of tag clouds while incorporating highly dynamic content include online news andminimal but sufficient indication of trends for a photo-sharing sites which serve freshly uploadedreasonable number of related tag clouds. and tagged material every day. Interesting discussions around tag clouds often include a seriesIndex Terms: Tag Clouds,Trend of tag clouds and consider how they evolve overvisualization,Multiple line graphs,Evaluation,Staked time. However, while tag clouds seem to invitebar charts. exposure of their evolution over time, they do not explicitly represent them. This results in a1 INTRODUCTION significant cognitive demand on people who want to Tag clouds have proliferated over the web Under stand how a tag cloud is evolved In thisover the last decade. They provide a visual summary paper, we introduce SparkClouds , a new breed ofof a collection of texts by visually depicting the tag tag cloud that incorporates sparklines with morefrequency by font size. In use, tag clouds can evolve typical tag cloud features to convey evidence ofas the associated data source changes over time change across multiple tag clouds. We also presentInteresting discussions around tag clouds often a controlled study that we conducted to compareinclude a series of tag clouds and consider how they SparkClouds with Parallel Tag Clouds (PTCs) (theevolve over time. However.since tag clouds do not only previous tag cloud visualization designed forexplicitly represent trends or support comparisons, understanding multiple tag clouds), as well as twothe cognitive demands placed on the person for traditional trend visualizations—multiple lineperceiving trends in multiple tag clouds are high. In graphs and stacked bar charts. We compared thesethis paper, we introduce SparkClouds, which four visualizations in terms of speed and accuracyintegrate sparklines into a tag cloud to convey in supporting three types of tasks (specific data,trends between multiple tag clouds. We present topic trends, and overview). We found thatresults from a controlled study that compares SparkClouds’ ability to show trends comparesSparkClouds with two traditional trend favourably to the alternative visualizations.visualizations—multiple line graphs and stacked bar Participants also preferred SparkClouds to stackedcharts—as well as Parallel Tag Clouds . Results bar charts and PTCs.show that SparkClouds’ ability to show trendscompares favourably to the alternative We organize this paper as follows. In thevisualizations. next section we outline the related work to provide Tag clouds are a text-based visual depiction context for our description of SparkClouds, whichof tags (or words), typically used to display the follows in Section 3. Section 4 describes the designrelative tag frequency, popularity, or importance by and results of the controlled study along with thefont size. They can also serve as a visual summary alternative visualizations we used in the study. Weof document content. In the last decade, tag clouds then conclude the paper with a discussion of the 1387 | P a g e
  • 2. G.Lakshmi, K.Rajendar, J.Pratap / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.1387-1392lessons learned from the study and suggestions for three types of search task; one of them was afuture work. standard list using uniform font size with wrapping . All but the traditional tag cloud worked best for2. RELATED WORK The origin of tag clouds goes back to 1976when an experiment was carried out by StanleyMilgram . A collective ―mental map‖ of Paris wascreated using font size to show how often each placewas mentioned as a landmark in the city. In 1997,Search Referral Zeitgeist was created by JimFlanagan as a way to visualize the number of timesa term was used to find a given website by font size.Among high-profile websites, Flickr used tagclouds first, followed by other Web 2.0 sites . Formore details about the history of tag clouds, see .Due to their astonishing popularity, there have beenmany efforts in exploring various properties of tagclouds. Several websites now enable people tocreate their own tag clouds from different types oftext sources . One interesting variation, showingtwo-word phrases, provides a quite differentperspective of the textby revealing themes in thecontent . There has been considerable research toimprove tag cloud layouts. Kaser and Lemireorganized tags in nested tables for HTML based Fig. 1. SparkClouds showing the top 25 words forsites by using an Electronic Design Automation the last time point(EDA) packing algorithm . Seifert et al. proposed a (12th) in a series. 50 additional words that are in thenew algorithm to address several issues found in the top 25 for thetraditional layouts . It creates compact and clear other time points can be (top) filtered out orlayouts by reducing whitespace and featuring (bottom) shown in grayarbitrary convex polygons to bound the terms. Tree at a smaller fixed-size font. (bottom) is used in theCloud arranges words on a tree to reflect their study.semantic proximity according to the text . one task. For the task of finding a specific tag, the list performed better than the tag cloud. Tag Maps employs a unique layout based Halvey and Keane compared tag clouds withon real geographical space . Wordle provides traditional lists (horizontal and vertical), each withremarkably distinctive layouts by utilizing regular vs. alphabetical order by asking participanttypography, color, and composition to balance to find a specific tag . They found that lists performvarious aesthetic criteria . Research efforts that better than tag clouds and that alphabetical orderattempt to understand the effectiveness and utility of further accelerates the search speed. Sinclair andtag clouds generally fall into one of two categories; Cardew-Hall conducted an experiment to investigatethose which investigate the visual features of tag the preference between a tag cloud and a traditionalclouds and those which compare tag clouds with search interface both for general browsing and fordifferent layouts. Bateman et al. compared nine information seeking tasks They found thatvisual properties of tag clouds for their effects on participants preferred the search interface forvisual search for tags . Their results show that font specific information retrieval tasks whereas the tagsize and font weight have stronger effects than cloud was preferred for more open-ended browsingothers such as color intensity, number of characters, tasks. In use, tag clouds can evolve as the associatedor tag area. Rivadeneira et al. conducted two data source changes over time. Interestingexperiments . In the first study, they examined the discussions around tag clouds often include a serieseffect of font size, location, and proximity to the of tag clouds and consider trends of their tags overlargest tag, asking participants to recall terms (for 60 time. This desire to study trends and understand howseconds) that were previously presented in tag text content or topics evolve over time has been theclouds (for 20 seconds). In the second study, they purpose of other visualizations such as theinvestigated the effect of bothfont size and word commonly used line graphs and bar charts.layout on users’ abilities to form an impression However, despite the significant amount of research(gist). From both studies, in accordance with on tag clouds, there has not been much research onprevious research, they observed a strong effect of how to visualize trends in tag clouds.font size. Many Eyes allows people to compare twoLohmann et al. compared four tag cloud layouts for texts in a single tag cloud . It uses two colors (one 1388 | P a g e
  • 3. G.Lakshmi, K.Rajendar, J.Pratap / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.1387-1392per tag cloud) and pairs the tags that appear in both 3.1 Scenariosclouds. While it enables easy comparison between 3.1.1 Keeping track of different non-familiar tagtwo tag clouds, this technique does not offer help in clouds Ramu is a stock market analyst. Every day,understanding trends over time as it is limited in the he has the same morning ritual. He spends about annumber of tag clouds visualized. Tagline Generator hour on the web to absorb the information requiredallows people to generate a sequence of tag clouds to keep up-to-date with the market. Is the newthat are associated with time, from a collection of product everyone is talking about out already? Whatdocuments ; a dynamic slider control is used to is the next big application that mobile users arenavigate the time points, but only one tag cloud is talking about? What are the reviews on the latestshown at a time. Parallel Tag Clouds (PTCs) is phone? Ramu has dozens of websites bookmarked,designed to provide an overview of a document but in fact, the majority of them are irrelevant today.collection by incorporating graphical elements of Indeed, he already knows a great deal ofparallel coordinates with the text size encoding of information and may already have consulted them intraditional tag clouds . While PTCs do show recent days. The real challenge for him is to identifymultiple clouds simultaneously, they do not and select which sites to dive into, to find where theexplicitly represent trends, and thus comparing new information is, and to locate any deepermultiple tag clouds to ascertain trends places the information he may need. Currently, Ramu’scognitive demands on the person. strategy is to read RSS feed titles and browse a dozen or so websites, many of which conveniently Cloudalicious is an online tool specifically present the current topics in a tag cloud form. Ramudesigned to visualize how tag clouds develop over likes these simple representations as they give him atime . For a given website, it downloads the tagging gist of the content of the website. He oftendata from del.icio.us and then graphs the collective remembers the large tags, but he still has troubleusers’ tagging activities over time using multiple spotting the new tags and topics, as well as keepingline graphs. While Cloudalicious clearly shows track of the less popular ones, especially because hesome trends, such as decay of the collective usage of sees many different tag clouds every day.tags, it may suffer from overlapping of lines anddoes not retain the visual appearance of tag clouds. 3.1.2 Monitoring familiar tag cloudsDubinko et al. presented a new approach to visualize Anjali is a researcher working as part of athe evolution of tags in Flickr using an animation 16-person team that is rapidly increasing in size.via Flash in a web browser . While they allow Right now, she works closely with 5 of her teampeople to observe and interact with the tags, their members and is relatively well-aware of theirmain contributions were not focused on the activities. But, as she juggles increasing numbers ofvisualization but rather on algorithms and data projects, she realizes that she cannot keep up-to-datestructures to generate the list of ―interesting‖ tags with the whole team. For example, it is quitefor a specific time period. To better convey the challenging for her to keep track of what isevidence of change across multiple tag clouds, we happening from the monthly meetings and weeklydeveloped a new breed of tag cloud called status reports. Indeed, she recently learned from herSparkClouds that integrates sparklines into a tag manager that she spent several days surveying acloud. We also conducted a controlled study to topic that one of the team members had already beenexplore the efficacy of SparkClouds by comparing working on for the past few weeks. To maintainit with two traditional trend visualizations, multiple awareness of the team activity, she generates tagline graphs and stacked bar charts, as well as with clouds from the weekly status reports. While theyPTCs. help her remember the key projects, she still has a difficult time noticing what has changed week-to-3 DESIGNING SPARKCLOUDS week, much less over longer spans of time. Being The basic idea behind SparkClouds is to able to compare these project tag clouds as theyretain the advantages of tag clouds while evolved might have helped highlight her colleague’sincorporating minimal but sufficient indication of shift in their work focus.trends for a reasonable number of related tag clouds.In particular, we focused on these advantages of tag 3.2 Design Rationale Summaryclouds: Compact use of space that can be flexibly A tag cloud is a visual representation that areorganized into different aspect ratios without broad range of people can easily decode, and makesnegatively impacting the readability of the cloud as effective use of display space. Our primary goala whole. Tag (or word) readability in that the with SparkClouds is to preserve these twoimportance or frequency of a tag is encoded directly characteristics, while incorporating the ability toin the size of the word. Since we based our design of convey trends. We also aim at supporting the twoSparkClouds on two usage scenarios, we first usage scenarios described above. Ramu is dealingdescribe these scenarios to provide the setting for with a large number of tag clouds; these may hangeour design development. radically and Ramu may not remember all topics in 1389 | P a g e
  • 4. G.Lakshmi, K.Rajendar, J.Pratap / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.1387-1392previous tag clouds. He needs to have an overview trends over time are the traditional line graphs andof the trends to understand the market at a high more recently stacked graphs . We selected thelevel. Anjali is familiar with the data. She has a simpler one of the two, sparklines, for use ingood memory of the simplified line graphs in the visualizing trends over time in SparkClouds.sense that axes are implied rather than explicitly Sparklines are simplified line graphs in the sensedrawn or labelled. They can be very compact and that axes are implied rather than explicitly drawn orstill provide an indication of a trend. As was also labelled. They can be very compact and stillshown in , this property made them attractive to use provide an indication of a trend. As was also shownas they can be inserted adjacent to each tag without in , this property made them attractive to use as theycluttering the entire presentation. previous tag can be inserted adjacent to each tag withoutclouds time-point-by-time-point and compare them cluttering the entire presentationto get a deeper understanding of what each persondid over time. A SparkCloud encodes the popularity Data Encoding: In SparkClouds, a sparkline depictsof tags by font size, as do standard tag clouds. To the popularity of the tag (vertical axis) over timeshow the trends in popularity of each tag over time, (horizontal axis). To maintain consistency in thewe introduce a second visual element adjacent to representation, the vertical axis of sparklines doeseach tag: a sparkline, .i.e. a minimal simplified line not encode the raw popularity of tags, but insteadchart uses a linear transformation function based on the relative popularity of tag. A potential refinement to3.2.1 Tag Clouds as Used in SparkClouds this approach could be to take advantage of the extra The tag cloud aspect of SparkClouds has precision offered by sparklines—if two wordtwo design parameters: the font size encoding and functionally map to the same font size, the sparklinelayout. whether one is slightly more frequent than can indicate whether one is slightly more frequentthe other. This may be useful when precisely than the other. This may be useful when preciselycomparing trends but we thought it was not needed comparing trends but we thought it was not neededfor our current usage scenarios. for our current usage scenarios.Representing Zero: To help people make Representing Zero: To help people makecomparisons between trends, we depict the comparisons between trends, we depict thehorizontal axis of each sparkline. This transforms horizontal axis of each sparkline. Thistransforms thethe sparkline into a sparkarea by filling the space sparkline into a sparkarea by filling the spacebetween the sparkline and the horizontal axis using between the sparkline and the horizontal axis usinga light gradient blue color . a light gradient blue color (Fig. 1). This visualFont Size Encoding:In traditional single tag cloud encoding helps in comparing sparklines that are notpresent. In the second method, the font size is used horizontally aligned with each other and givesto encode the frequency of tags at a given time additional visual assistance in identifying thepoint. In this view, Anjali is able to identify at a periods during which a tag was not By glancing atglance her team members’ most popular topics for the sparkline below a given tag, Ramu and Anjalieach time point. This view is also more appropriate can assess if it is new, if its popularity has beenfor routine review, as it most clearly depicts the stable or when it experienced a spike in popularity.activity at a given time point. With this method, thefont size is stable for each tag in that it does not 3.2.3 Unifying Tag and Sparkline:change whether the visualization shows either one Given that we introduced an additionalor several tag clouds. However, this encoding visual element for each tag, we broke themakes tags between tag clouds comparable only in ―homogeneity‖ of the tag cloud. To help peoplerank not in frequency. While SparkClouds, by perceive the two visual elements (tag and sparkline)default, use per time point font size encoding, they as a single unit of information, we consideredallow people to select a more appropriate encoding several possibilities .Alignment: Sparklines can be(or normalization) method according to their task as placed before. We experimented with using a scriptPTCs do. (handwriting) font to provide visual continuity, butLayout: As described above, there has been much we thought that the legibility of the tag wasresearch on laying out tag clouds . Even though we compromised . We also tried using an explicitpresent the design of SparkClouds as having an baseline and aligning both text and sparkline on thealphabetical order throughou the paper, it can baseline, but decided against this idea as itsupport any existing tag cloud layout because introduced too much clutter.SparkClouds retains the same structure as Overlays: We explored overlaying the tag over theconventional tag clouds. sparkline . These representations appeared too cluttered and did not work well in practice since3.2.2 Sparklines words vary widely in length; this made it difficult to The most common visual encodings of compare points in time between two words whose 1390 | P a g e
  • 5. G.Lakshmi, K.Rajendar, J.Pratap / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.1387-1392sparklines spread across different scales. In addition, visualizations, all 75 top words were shown, clearlywe thought that text overlays, even with light font indicating which were the top 25 words for eachand white outlines, made the words less readable month. In Parallel Tag Clouds, since the top s for(especially when the font size is small). each month are displayed simultaneously in theMirror: To avoid the clutter caused by the overlays, column for their month, all words are shown andwe tried to mirror the line chart and place it under some words are shown in multiple columns. Thethe word . We decided against this option as we three other visualizations display all the top 75 mostbelieved it may compromise the decoding of the frequent words and highlight only the words thatsparkline and thus be misleading. Indeed, even with were included in the top 25 for the selected month.various background and line-color options, wetended to interpret the mirrored sparkline as 4.3.1 Multiple Line Graph (MultiLine)standard non-mirrored ones. A line graph explicitly shows trends (i.e.,Foreground and background colors: We first how a value changes) by connecting a series ofexplored using two foreground colors, which successive data points; usually the x-axis representsalternated between adjacent terms (but coloring the time. While a multiple line graph helps peopletags and associated sparkline with the same color). compare trends between multiple variables, it oftenThis solution worked quite well, but it looked more suffers from overlapping when many lines arecluttered than the one with a single color. We also displayed at once. To alleviate this problem, wethought that we could use color more implemented the multiple line graph in theeffectively for other purposes. In Swapna’s scenario, following way. While all the top 75 most frequentfor example, we words are displayed, only the words that were(a) align before included in the top 25 for the selected month are(b) align after highlighted . Participants can select a time point by(c) align above (d) overlay (e) mirror clicking on the label shown at the bottom of the visualization. The currently selected time point is marked with blue background and a thick border. When participants move the mouse over a line or a word in the legend list box at the top, we highlight(a) (b) only the focused word and the line. When the values overlap, we slightly shift the data point diagonally (2 pixels to the right and below). We used 5 distinctive colors to help participants better differentiate the lines.(c) (d)(e)4.3 Visualizations We compared four visualizations:SparkCloud, Multiple Line Graph, Parallel TagCloud, and Stacked Bar Chart (see Figs 1, 3, and 4).We chose multiple line graphs and stacked barcharts because they are commonly used in manytools to show trends . We chose Parallel Tag Cloudsbecause they are the only tag cloud specificallydesigned to support cross tag cloud comparison formore than two tag clouds.25 word While each of these visualizations isinherently different from one another, when possiblewe implemented the visualizations based on thesame visual guidelines. For example, words arepresented in an alphabetical order in all fourvisualizations. SparkClouds and Parallel TagClouds share the same range of font sizes (from 10to 34), and Multiple Line Graphs and Stacked BarCharts use the same font size (15). For all 1391 | P a g e
  • 6. G.Lakshmi, K.Rajendar, J.Pratap / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.1387-13924.3.2 Stacked Bar Chart (StackedBar) Conclusion Stacked bar charts, in which bars are The disadvantage of the tag clouds coulddivided into nominal variables, are commonly used be overcome by using spark clouds. In this paper,to show trends. ThemeRiver is a timeline we have described SparkClouds, a novelindicating the flow of document themes. It uses visualization that incorporates sparklines into a tagwidth of the river to show the number of documents cloud to represent trends across a series of tagand the river is sub-divided by topics, which ebb clouds; SparkClouds inherit advantages from bothand flow over time. The Name Voyager visualizes a sparklines and tag clouds. First, with sparklines,graph of the popularity of baby names over the past SparkClouds effectively provide people with ancentury]. Both of these examples use smoothly overview of trends using very little additional space.connecting lines between the data points. In our Second, because it is still in the form of tag clouds,implementation we kept the adjacent bars discrete to SparkClouds offer a compact and aestheticallymake individual data values more readable. While pleasing layout and can be used in place ofstacked bar charts are particularly good for traditional tag clouds. We have also described theconveying at cumulative and overall trends, we design of SparkClouds along with usage scenarios.identified two major issues with standard stackedbars. First, they may be deceiving for evaluating REFERENCEStends across time for a single term because at any 1) Visualizing Translation Variation: Othello :given time point the placement of neighboring terms A Survey of Text Visualization and Toolsinterferes with (or rather, has a displacement effect Zhao Geng, Robert S.Laramee, Tomon) the placement of the series of interest. Second, Cheesman, Andy Rothwell, David M.label placement is non-trivial because each tag Berry, Alison Ehrmann, Swansearequires a position that is large enough to ensure the University, 2011label is readable, which is not always possible if a 2) ManiWordle: Providing Flexible Controltag generally has a low popularity; furthermore, over Wordle Kyle Koh, Bongshin Lee,labels are not guaranteed to be vertically or Bohyoung Kim, and Jinwook Seohorizontally aligned, making scanning difficult. 3) Marketspace Envisioning the Cloud:TheBoth of these issues are problematic for tag clouds Next Computing Paradigm March Jeffreysince readability is of critical importance to F. Rayport ,Andrew Heyward.investigate trends in tags over time. To address these 4) ABC News – Tag Cloud – News topicsissues, we modified the standard stacked bar in the organized to show what’s in today’sfollowing way. The tags are shown as a vertical list headlines,on the left, each of which is accompanied with a http://www.abc.net.au/news/tag/cloud.htm(horizontally) stacked bar (Fig. 3b). This stacked bar 5) S. Bateman, C. Gutwin, and M. Nacenta,for each tag is created by horizontally stacking ―Seeing things in the clouds: the effect ofindividual bars for each month. To help people visual features on tag cloud selections,‖compare bars for a particular month, stacked bars Procan be interactively aligned to the left side of the 6) P. Bausch and J. Bumgardner, Flickrbars for the selected month. We also drew a baseline Hacks. OReilly Press, pp. 82-86, 2006.starting from the time point label. 1392 | P a g e