Iterative Integration of Visual Insights during Scalable Patent Search and Analysis

Koch, Steffen; Bosch, Harald; Giereth, Mark; Ertl, Thomas

doi:10.1109/tvcg.2010.85

Cited by 33 publications

(15 citation statements)

References 25 publications

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“…There are further visual approaches that particularly address scientific document retrieval. Koch et al [28] support patent retrieval based on content and metadata queries and visual interactive techniques for query widening. Beck at al.…”

Section: Related Workmentioning

confidence: 99%

CiteRivers: Visual Analytics of Citation Patterns

Heimerl

Han

Koch

et al. 2016

IEEE Trans. Visual. Comput. Graphics

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The exploration and analysis of scientific literature collections is an important task for effective knowledge management. Past interest in such document sets has spurred the development of numerous visualization approaches for their interactive analysis. They either focus on the textual content of publications, or on document metadata including authors and citations. Previously presented approaches for citation analysis aim primarily at the visualization of the structure of citation networks and their exploration. We extend the state-of-the-art by presenting an approach for the interactive visual analysis of the contents of scientific documents, and combine it with a new and flexible technique to analyze their citations. This technique facilitates user-steered aggregation of citations which are linked to the content of the citing publications using a highly interactive visualization approach. Through enriching the approach with additional interactive views of other important aspects of the data, we support the exploration of the dataset over time and enable users to analyze citation patterns, spot trends, and track long-term developments. We demonstrate the strengths of our approach through a use case and discuss it based on expert user feedback.

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Section: Related Workmentioning

confidence: 99%

CiteRivers: Visual Analytics of Citation Patterns

Heimerl

Han

Koch

et al. 2016

IEEE Trans. Visual. Comput. Graphics

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“…A natural source for analogical stimuli is the U.S. patent database, which is the source of analogies for the work presented here, as well as a great deal of other research, including TRIZ [33] using heuristic rules to help engineers overcome impasses in functional reasoning by searching through patents; an axiomatic conceptual design tool [34] combining TRIZ and functional basis; patent mining [35][36][37] characterizing them by citations, claims, average number of words per claim, number of classes that the patent spans, etc. ; design repository work incorporating function-based search using Chi Matrix and Morphological Matrix techniques [38]; PatViz [39], allowing for visual exploration of iterative and complex patent searches and queries using all types of patent data, including full text, which relies on structures that are either predefined or userdefined classification schemes; patent database search using a mapped functional basis [40]; a BioMedical Patent Semantic Web [41] finding semantic associations between biological terms within biomedical patent abstracts and returning a ranked list of patent resources and a fully connected Semantic Web that displays the relationships between the important terms and between resources; and a topic model based taxonomy or hierarchical structure only used to categorize the remaining documents into "topics" [42]. Our work is differentiated from these efforts in that it focuses on using the full textual content of the patents, which it is hoped will allow for richer outcomes, on structuring design repositories and more open ended analogical transfer, and on multiple structure types generated using a hierarchical Bayesian algorithm.…”

Section: Computational Design Toolsmentioning

confidence: 99%

The Meaning of “Near” and “Far”: The Impact of Structuring Design Databases and the Effect of Distance of Analogy on Design Output

Chan

Cagan

et al. 2013

Journal of Mechanical Design

207

134

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This work lends insight into the meaning and impact of "near" and "far" analogies. A cognitive engineering design study is presented that examines the effect of the distance of analogical design stimuli on design solution generation, and places those findings in context of results from the literature. The work ultimately sheds new light on the impact of analogies in the design process and the significance of their distance from a design problem. In this work, the design repository from which analogical stimuli are chosen is the U.S. patent database, a natural choice, as it is one of the largest and easily accessed catalogued databases of inventions. The "near" and "far" analogical stimuli for this study were chosen based on a structure of patents, created using a combination of Latent Semantic Analysis and a Bayesian based algorithm for discovering structural form, resulting in clusters of patents connected by their relative similarity. The findings of this engineering design study are contextualized with the findings of recent work in design by analogy, by mapping the analogical stimuli used in the earlier work into similar structures along with the patents used in the current study. Doing so allows the discovery of a relationship between all of the stimuli and their relative distance from the design problem. The results confirm that "near" and "far" are relative terms, and depend on the characteristics of the potential stimuli. Further, although the literature has shown that "far" analogical stimuli are more likely to lead to the generation innovative solutions with novel characteristics, there is such a thing as too far. That is, if the stimuli are too distant, they then can become harmful to the design process. Importantly, as well, the data mapping approach to identify analogies works, and is able to impact the effectiveness of the design process. This work has implications not only in the area of finding inspirational designs to use for design by analogy processes in practice, but also for synthesis, or perhaps even unification, of future studies in the field of design by analogy.

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“…Wongsuphasawat et al [WL14] incorporates both filtering options but in two different tools focusing on very specific tasks of comparing datasets and funnel analysis. PatViz [KBGE11] incorporates visual queries and multiple ways of viewing the data but is very specific to patent data.…”

Section: Related Workmentioning

confidence: 99%

Segmentifier: Interactive Refinement of Clickstream Data

Dextras-Romagnino

Munzner

2019

Computer Graphics Forum

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Clickstream data has the potential to provide insights into e‐commerce consumer behavior, but previous techniques fall short of handling the scale and complexity of real‐world datasets because they require relatively clean and small input. We present Segmentifier, a novel visual analytics interface that supports an iterative process of refining collections of action sequences into meaningful segments. We present task and data abstractions for clickstream data analysis, leading to a high‐level model built around an iterative view‐refine‐record loop with outcomes of conclude with an answer, export segment for further analysis in downstream tools, or abandon the question for a more fruitful analysis path. Segmentifier supports fast and fluid refinement of segments through tightly coupled visual encoding and interaction with a rich set of views that show evocative derived attributes for segments, sequences, and actions in addition to underlying raw sequences. These views support fast and fluid refinement of segments through filtering and partitioning attribute ranges. Interactive visual queries on custom action sequences are aggregated according to a three‐level hierarchy. Segmentifier features a detailed glyph‐based visual history of the automatically recorded analysis process showing the provenance of each segment as an analysis path of attribute constraints. We demonstrate the effectiveness of our approach through a usage scenario with real‐world data and a case study documenting the insights gained by a corporate e‐commerce analyst.

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Iterative Integration of Visual Insights during Scalable Patent Search and Analysis

Cited by 33 publications

References 25 publications

CiteRivers: Visual Analytics of Citation Patterns

CiteRivers: Visual Analytics of Citation Patterns

The Meaning of “Near” and “Far”: The Impact of Structuring Design Databases and the Effect of Distance of Analogy on Design Output

Segmentifier: Interactive Refinement of Clickstream Data

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