PhD Thesis Review, No.5

学位論文紹介A Study on Structural and
Semantic Analysis for
Presentation Content
Management
Yuanyuan WANG
With the advent of Web services such as MOOC (e.g.,
Coursera, iTunes U) and presentation sharing websites(e.g., SlideShare, Prezi), to store presentation contents
that they use in speeches and lectures owing to thefeatures for searching, browsing, reusing, and sharing.
For example, famous Coursera and SlideShare provide an
online presentation archive for self-learning and later
review. Although these tools and Web services make iteasy for creating and sharing presentation contents arewidely used, criticisms have pointed out their problems
from the viewpoint of understandability about relevant
information, structural information, and contextual
information of presentation contents. In this research, weare challenging to support for retrieval, generation,
grasping overviews of presentation contents by focusing
three critical issues, that is, a) determining semantic
relationships, b) extracting expression styles, and c)presenting presentation context in presentation contents.

1. Introduction
Due to the advent of usable presentation tools to create
attractive presentation contents, such as Microsoft
PowerPoint and Apple Keynote, presentations now play asocially important role in promoting understanding inmany fields, including business and education. Many
people have used Web services such as presentation
sharing websites (e.g., SlideShare 1, Prezi 2 ) and MOOC
(e.g., Coursera3, iTunes U4) to store presentation contents
that they use in speeches and lectures owing to thefeatures for editing, browsing, sharing, and reusingpresentation data. For example, most presentation
contents with rich graphics and animations are preparedby using presentation tools, i.e., Microsoft PowerPoint,
Apple keynote, and recently Prezi. In addition,
presentation sharing websites such as SlideShare andCoursera provide an online presentation archive for later
review with slides or video recordings of speeches.
Although useful and powerful support tools make iteasy for creating presentation contents and Web services
for sharing the presentation contents are widely used,criticisms have pointed out their problems from theFig.1 Concept of a structural and semantic analysis ofpresentation contents
viewpoint of understandability of the presentation
contents [1, 2]. They are still a lack of support for users to(1) acquire relevant information implicit among thepresentation contents; (2) utilize structural information
explicit in the presentation contents; and (3) grasp
overviews of contextual information existing in thepresentation contents. This research addresses these
problems for improving understanding of presentation
contents, enhancing user interactions through thepresentation contents by analyzing structural and lexical
semantics in the presentation contents. In this doctoral
dissertation, we are challenging to support for retrieval,
generation, grasping overviews of presentation contents
by focusing three critical issues, that is, a) determining
semantic relationships, b) extracting expression styles,
and c) presenting presentation context as shown in Fig.1.
This article is organized as follows. Section 2 describes
our approaches and reviews related work. Section 3
explains methods to support for slide retrieval to readers
or searchers by utilizing semantic relationships between
slides. Section 4 describes a method to support for slide
generation from textbook chapters to presenters or
authors by reusing expression styles of existing slides.
Section 5 presents methods to support for graspingoverviews of presentation contents to readers byvisualizing presentation context. Finally, Section 6
concludes this research with future direction of theresearch.

2. Our Approaches and Related Work
In order to provide a presentation content management
for next-generation presentation contents, we have toconsider the emerging issues:Regular Member. Faculty of Computer Science andEngineering, Kyoto Sangyo University
circl.wang@gmail.com
SlideShare: http://www.slideshare.net/.
Prezi: http://prezi.com/.
3 Coursera: http://www.coursera.org/.
4 iTunes U: http://www.apple.com/jp/education/itunes-u/.
1
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学位論文紹介Fig.2 Concept of learning channel generation

Fig.3 Concept of slide ranking and snippet generationa) Determining semantic relationships
Support for presentation content retrieval to readers or
searchers, we need to explore how to determine semantic
relationships implicit among presentation contents. To
difficulty of determine the semantic relationships, forinstance, we develop a metadata extraction method toanalyze two important features of metadata in thepresentation contents: one is structural semantics thatstructured segments (i.e. itemized sentences of bullet
points in slides), the other one is lexical semantics thatsemantic relations implicitly exist between keywords (i.e.
an is-a, a part-of relations). In this way, it can help
readers or searchers understand relevant information ofpresentation slides well.
b) Extracting expression styles
Support for presentation content generation topresenters or authors, we need to analyze various
expression styles of existing presentation slides. To
difficulty of extract the expression styles, in general,
slides are made from documents of a textbook for lectures.
Then, we defined expression styles of slides that levels ofwords are located in slides based on the slide structuresfrom documents. Therefore, expression styles whichcontain words from the documents are located in whichlevel positions of which slides. In this way, it can help
presenters or authors generate presentation slides indesired expression styles of existing presentation slides.
c) Presenting presentation context
Support for grasping overviews of presentation
contents to readers, we need to analyze and present
presentation context of presentation contents intuitively.
To difficulty of present the presentation context, forinstance, in order to provide an overview of presentation
slides, we adopt a word cloud visualization of presentation
slides that words related to the context are important; andwe also visualize presentation slides in a structural layout.
In this way, it can help readers interactively and easily
grasp overviews of presentation content well.

only the important slides decreases the relevance of theresults of a query to the given context.
Several studies related to slide-making support havefocused on reusing documents (i.e., academic papers,
textbooks). Mathivanan et al. [5] and Miyamoto et al. [6]proposed a system for generating slides from academic
papers. Their methods summarize and extract
information from an academic paper by TF-IDF scores.
From the viewpoint of reusing slides, Sharmin et al. [7]and Mejova et al. [8] proposed a system for composing
slides from existing ones and modifying them. We share acommon point in reusing expressions of words in existingslides to create new ones.
In the area of information visualization, several studies
have concentrated on representing text content at theword or phrase level, including TextArc (www.textarc.org)
and Phrase Net [9]. Our work focuses on visualizing
presentation contents in word clouds with transitions forreflecting
presentation
context.
Inaddition,
NextSlidePlease [10] creates and delivers presentations ina nonlinear fashion. The Fly application addressesgraph-based presentation authoring [11]. Our work issimilar to these works, as we utilize a structural layout
with a ZUI, to allow interactive and collaborative
browsing by users for each other.

2.2 Related Work
Most of the research related to slide retrieval. Yokota etal. [3] proposed a system named UPRISE for retrieving
important slides from archives containing a combinationof lecture slides and recorded videos. Le et al. [4]generated digests of recorded lecture videos by using
important slides. However, we considered that retrieving

3. Presentation Content Retrieval
We propose methods to support for slide retrieval toreaders or searchers by utilizing semantic relationships
between slides. Concretely, we measure semantic
importance and relationships with semantic relations
between keywords and document structure inpresentation contents; i) scene combination for slides withrecorded videos and ii) semantic ranking and context
summarization of slides.
As for i), we propose a method to automaticallygenerate learning channels by using the semantic
relationships among scenes, which lets users easily focus
on either highly detailed scenes or introductory scenes
without needing to examine all of the data (see Fig.2). As
depicted in Fig.3, in the case of ii), we attempt to rankslides by using the semantics of relationships without
relying on the existence of any specific structure in a slideor relevant information between slides. In addition, we
consider that retrieved slides also contain irrelevant

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学位論文紹介Fig.4 Concept of slide outline generation
information to a query. For this, we challenge to generatesnippets that capture relevant portions of the retrieved
slides as their surrounding context, which help users
understand them in presentation contents easily.

3.1 Scene Combination for Slides with Videos
We developed a system of automatically generating
learning channels for readers to extract scenes andcombined scenes from slides with their recorded video
based on semantic relationships. The system analyzed thetypes of semantic relationships on the basis of themetadata of structural information, such as indents andtexts in slides, and the text of speech in the video. In thisway, our newly generated learning channels let users
easily focus on either highly detailed or introductoryslides without needing to examine all of the data. In thiswork, we could show that there is a possibility to utilize
the semantic relationships analyzed by exploiting
heterogeneous media features of presentation contents.

3.2 Slide Ranking and Snippet Generation
We built a slide retrieval system for searchers involving
1) semantic ranking by considering what rank orders of
the slides related to a query, and 2) snippet generation, byconsidering what portions of the slides are relevant to thequery, on the basis of the relationships between slides.
These methods are based on the keyword conceptual
structure of the semantic relations that implicitly exist
between keywords, and the document structure of theindent levels in the slides. With our novel 1) slide ranking
method and 2) snippet-generation method, not only
precise retrieve target slides but also the semantic
ranking of them, thus ranking either highly detailed
slides or generalized slides in an order to help users easily
learn through the slides; and the relevant portions ofthem in the presentation by focusing on portions fromeither detailed or generalized slides, thus giving theirsurrounding context to help users easily determine which
the slides to learn are useful or not. Finally, we cloud show
the effectiveness of our methods that enable the users tobrowse slide rankings and snippets of the retrieved slides
efficiently and effectively.

4. Presentation Content Generation
We propose a method to support for slide generationfrom textbook chapters to presenters or authors byreusing expression styles of existing slides (see Fig.4).
Although most slides can be automatically generated byconventional methods follow structured document

Fig.5 Concept of dynamic word cloud generation
summaries (e.g. academic papers), we aim to organize
slide layouts from target chapters by reusing various
styles of referred slides based on level positions of words.
Therefore, we analyze level positions of words in thereferred slides and arranged the words from target
chapters to generate slide outlines based on difference indocument structure (i.e. text structure within a chapter,slide structure within a slide). To achieve this, we extract
differences between tendency of word appearance in thechapters and their slides (referred slides). This method
generated slide outlines by using the expression styles of
the corresponding words from the target chapters in thesame layouts as that of the referred slides. Finally, we
could show the possibility to generate slide outlines byreusing the expression styles of the existing slides.

5. Grasping Overviews of Presentation
Contents
We propose a method to visualize presentation contents
by extracting words important to the context ofpresentations. Here, we focus on how to decide which files
are worth learning, because most of presentation contents
in search results are similar; it can be difficult to identify
differences in them. Therefore, we propose a method togenerate dynamic word clouds of presentation contents bypresenting presentation context (see Fig.5). In addition,
we propose a collaborative browsing platform thatgenerates a meaningfully structured presentation called
iPoster by using slides (see Fig.6). It promotes userinteraction and communication.

5.1 Dynamic Word Clouds of Slides
We developed a quick browsing interface to help
readers easily and effectively grasp overviews ofpresentation contents. For the purpose, we provide a word
cloud visualization that summarizes information to help
the users visually understand the context of eachpresentation. Words important to the presentation context,
is first extracted based on components of the presentation
content (i.e., slide structure and links between slides). In
order to generate dynamic word clouds of slides, weweight extracted words from presentation context, andthen present transitions that highlight the semantic

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学位論文紹介that support for retrieval, generation, and graspingoverviews of presentation contents.
In the future, we will further study on Next-generation
Presentation Data Analytics and Advanced Management.
By stepping into analyses for human-computerinteraction (HCI) and collaborations through presentation
contents, we plan to develop advanced applications which
are efficient and useful in education area, such as
self-learning navigation, social learning, and gamification.

[References］

Fig.6 Concept of a collaborative browsing platform
relationships between the slides. Finally, we were able toconfirm that our dynamic word clouds help readers easily
and effectively understand the context of slides.

5.2 iPoster: A Collaborative Browsing Platform
Recently, zoomable presentations as a substitute to
traditional presentations that allow users to zoom in andout of the presentation media. Then, we built acollaborative browsing platform for presentation slides
based on interactive poster generation, called iPoster, forpresenting elements (i.e., textual and graphic elements) ina meaningfully structured layout with automatictransitions, such as zooms and pans, to promote userinteraction. Especially, we propose a semantic structure
analysis model for extracting elements and determining
the semantic relationships between the elements of theslides. In order to provide an overview of presentation
slides, we initially place the elements in a tree structure
combined with a stacked Venn. We then attach thezooming and panning transitions between the elements,
based on the semantic relationships. Finally, we were able
to confirm that iPoster helps readers to interactively andcollaboratively browse, and understand educationalpresentations easily and efficiently using their tablets. A
collaborative browsing platform based on the iPoster,which can share and navigate information, matches eachuser’s specific requirements by analyzing the users’
operations. Further, it detects other users who have
similar requirements by mapping the similarity in theiroperations and conveys their interests to each other.

6. Conclusions
In this research, in order to management ofpresentation contents, we studied on a structural andsemantic analysis of relevant information, structural
information, and contextual information in presentation
contents. For this, we proposed three approaches: a) we
explored semantic relationships inside between slides orscenes; b) we analyzed expression styles of existing slides;c) we presented presentation context intuitively. As awhole, we were able to confirm that our approaches
enable us to advance next-generation presentation
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