Session:「Visualization of Space and Shape」

TopoText: Context-Preserving Text Data Exploration Across Multiple Spatial Scales

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3173611

論文アブストラクト: TopoText is a context-preserving technique for visualizing text data for multi-scale spatial aggregates to gain insight into spatial phenomena. Conventional exploration requires users to navigate across multiple scales but only presents the information related to the current scale. This limitation potentially adds more steps of interaction and cognitive overload to the users. TopoText renders multi-scale aggregates into a single visual display combining novel text-based encoding and layout methods that draw labels along the boundary or filled within the aggregates. The text itself not only summarizes the semantics at each individual scale, but also indicates the spatial coverage of the aggregates and their underlying hierarchical relationships. We validate TopoText with both a user study as well as several application examples.

日本語のまとめ:

空間集合体のテキストデータを地図上に視覚化、空間現象の洞察を得るためのコンテキスト保存技術TopoTextの開発。テキストラベルの色、不透明度、密度および方向性についての異なるデザインを比較、評価した。

HomeFinder Revisited: Finding Ideal Homes with Reachability-Centric Multi-Criteria Decision Making

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3173821

論文アブストラクト: Finding an ideal home is a difficult and laborious process. One of the most crucial factors in this process is the reachability between the home location and the concerned points of interest, such as places of work and recreational facilities. However, such importance is unrecognized in the extant real estate systems. By characterizing user requirements and analytical tasks in the context of finding ideal homes, we designed ReACH, a novel visual analytics system that assists people in finding, evaluating, and choosing a home based on multiple criteria, including reachability. In addition, we developed an improved data-driven model for approximating reachability with massive taxi trajectories. This model enables users to interactively integrate their knowledge and preferences to make judicious and informed decisions. We show the improvements in our model by comparing the theoretical complexities with the prior study and demonstrate the usability and effectiveness of the proposed system with task-based evaluation.

日本語のまとめ:

地理的に理想的な住居の探索を行うシステムの提案。タクシーの軌道データを利用して得られた関心施設へのアクセス可能性を基本とし、視覚的分析システムを用い対話的にユーザの嗜好に沿うフィルタリング、評価を行う。

TopicOnTiles: Tile-Based Spatio-Temporal Event Analytics via Exclusive Topic Modeling on Social Media

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3174157

論文アブストラクト: Detecting anomalous events of a particular area in a timely manner is an important task. Geo-tagged social media data are useful resource for this task; however, the abundance of everyday language in them makes this task still challenging. To address such challenges, we present TopicOnTiles, a visual analytics system that can reveal information relevant to anomalous events in a multi-level tile-based map interface by using social media data. To this end, we adopt and improve a recently proposed topic modeling method that can extract spatio-temporally exclusive topics corresponding to a particular region and a time point. Furthermore, we utilize a tile-based map interface to efficiently handle large-scale data in parallel. Our user interface effectively highlights anomalous tiles using our novel glyph visualization that encodes the degree of anomaly computed by our exclusive topic modeling processes. To show the effectiveness of our system, we present several usage scenarios using real-world datasets as well as comprehensive user study results.

日本語のまとめ:

ソーシャルメディアデータから特定のエリアの異常イベントを検出するシステムの提案。ジオタグ付きのツイートから独自のトピックモデリングにより検出された時空間的に排他的なトピックをタイルベースで地図上に表示する。

To Distort or Not to Distort: Distance Cartograms in the Wild

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3174202

論文アブストラクト: Distance Cartograms (DC) distort geographical features so that the measured distance between a single location and any other location on a map indicates absolute travel time. Although studies show that users can efficiently assess travel time with DC, distortion applied in DC may confuse users, and its usefulness "in the wild" is unknown. To understand how real world users perceive DC's benefits and drawbacks, we devise techniques that improve DC's presentation (preserving topological relationships among map features while aiming at retaining shapes) and scalability (presenting accurate live travel time). We developed a DC-enabled system with these techniques, and deployed it to 20 participants for 4 weeks. During this period, participants spent, on average, more than 50% of their time with DC as opposed to a standard map. Participants felt DC to be intuitive and useful for assessing travel time. They indicated intent in adopting DC in their real-life scenarios.

日本語のまとめ:

現在地と他の場所との測定距離が絶体移動時間を示すよう地理的特徴を歪めて作られた地図Distance Cartogramを事前知識の無いユーザが混乱無く利用できるよう開発した2つのアルゴリズムの提案及び評価。