Word clouds have become one of the most widely accepted visual resources for document analysis and visualization, motivating the development of several methods for building layouts of keywords extracted from textual data. Existing methods are effective to demonstrate content, but are not capable of preserving semantic relationships among keywords while still linking the word cloud to the underl...

Word cloud is a popular text visualization technique that extracts keywords from and displays them on the 2D space aesthetically. Word often used to display contents, aid analysis attract readers. In this work, design of word introduced three aspects: visual encoding, layout interaction. Then current researches are summarized by four categories: semantic clouds, shape-constrained ...

Search engine result pages (SERPs) are known as the most expensive real estate on the planet. Most queries yield millions of organic search results, yet searchers seldom look beyond the first handful of results. To make things worse, different searchers with different query intents may issue the exact same query. An alternative to showing individual web pages summarized by snippets is to repres...

Word cloud is a visualization form for text that is recognized for its aesthetic, social, and analytical values. Here, we are concerned with deepening its analytical value for visual comparison of documents. To aid comparative analysis of two or more documents, users need to be able to perceive similarities and differences among documents through their word clouds. However, as we are dealing wi...

                                                                                                                                                                                                                       Vocabulary is an important component in all four skills of language. Issue of vocabulary retention has great importance to EFL teachers in instructional contexts because they always ...

With the advent of online education services such as iTunes U and SlideShare, students are able to access various presentation files from many universities for study purposes. However, self-learners retrieving such files still need support to decide which files in candidate presentations are worth learning because most of the candidates are similar; it can be difficult to identify differences i...

We present txt2vz (txt2vz.appspot.com), a new tool for automatically generating a visual summary of unstructured text data found in documents or web sites. The main purpose of the tool is to give the user information about the text so that they can quickly get a good idea about the topics covered. Txt2vz is able to identify important concepts from unstructured text data and to reveal relationsh...

Language resources are often compiled for the purpose of variational analysis, such as studying differences between genres, registers, and disciplines, regional and diachronic variation, influence of gender, cultural context, etc. Often the sheer number of potentially interesting contrastive pairs can get overwhelming due to the combinatorial explosion of possible combinations. In this paper, w...

The University of Otago submitted runs to the Snippet Retrieval Track and the Relevance Feedback tracks at INEX 2011. Snippets were generated using vector space ranking functions, taking into account or ignoring structural hints, and using word clouds. We found that using passages made better snippets than XML elements and that word clouds make bad snippets. In our runs in the Relevance Feedbac...

We study the problem of computing semantics-preserving word clouds in which semantically related words are close to each other. We implement three earlier algorithms for creating word clouds and three new ones. We define several metrics for quantitative evaluation of the resulting layouts. Then the algorithms are compared according to these metrics, using two data sets of documents from Wikiped...