Use of Freely-Available Weebly in Creating Quick and Easy Web Pages: poster presentation

Weebly is a freely-available software for creating Web pages without having to know HTML. It is easy to use, with its drag and drop editor, and offers the ability to add documents, Web links, videos, slideshows, audio, forms, polls, etc. It is hosted by Weebly and has no limits on storage space. Many templates are available for Web page design. One can publish and update almost immediately. Combined with usage of the freely-available Google Analytics, for example, it is possible to gather usage statistics. The site can be password protected, if need be. Weebly for Education is a special version for teachers and schools.

Voices for writing essays, reports, web pages, blogs etc.

Looks at the different ways we write for different audiences.

Evaluating the prevalence, content and readability of complementary and alternative medicine (CAM) web pages on the internet.

Complementary and alternative medicine (CAM) use is growing rapidly. As CAM is relatively unregulated, it is important to evaluate the type and availability of CAM information. The goal of this study is to deter-mine the prevalence, content and readability of online CAM information based on searches for arthritis, diabetes and fibromyalgia using four common search engines. Fifty-eight of 599 web pages retrieved by a "condition search" (9.6%) were CAM-oriented. Of 216 CAM pages found by the "condition" and "condition + herbs" searches, 78% were authored by commercial organizations, whose pur-pose involved commerce 69% of the time and 52.3% had no references. Although 98% of the CAM information was intended for consumers, the mean read-ability was at grade level 11. We conclude that consumers searching the web for health information are likely to encounter consumer-oriented CAM advertising, which is difficult to read and is not supported by the conventional literature.

Use and abuse of audivisual media in the college classroom. Slides show and web pages

The multimedia development that has taken place within the university classrooms in recent years has caused a revolution at psychological level within the collectivity of students and teachers inside and outside the classrooms. The slide show applications have become a key supporting element for university professors, who, in many cases, rely blindly in the use of them for teaching. Additionally, ill-conceived slides, poorly structured and with a vast amount of multimedia content, can be the basis of a faulty communication between teacher and student, which is overwhelmed by the appearance and presentation, neglecting their content. The same applies to web pages. This paper focuses on the study and analysis of the impact caused in the process of teaching and learning by the slide show presentations and web pages, and its positive and negative influence on the student’s learning process, paying particular attention to the consequences on the level of attention within the classroom, and on the study outside the classroom. The study is performed by means of a qualitative analysis of student surveys conducted during the last 8 school Civil Engineering School at the Polytechnic University of Madrid. It presents some of the weaknesses of multimedia material, including the difficulties for students to study them, because of the many distractions they face and the need for incentives web pages offer, or the insignificant content and shallowness of the studies due to wrongly formulated presentations.

Mobile Access to Cultural and Historical Heritage Web Pages

The main focus of attention in this paper is the access to websites of leading regional, national and world museums. Their accessibility from desktop and mobile devices is hereby evaluated. The paper covers a detailed analysis of the mobile operating systems, their market share in Bulgaria and the opportunities they offer to the users. The need for contemporary cultural and historical heritage websites which maintain lighter but fully-functioning mobile versions, facilitating and making their access from portable devices easier, is also well-grounded here.

Web Data Extraction from Query Result Pages Based on Visual and Content Features

A rapidly increasing number of Web databases are now become accessible via
their HTML form-based query interfaces. Query result pages are dynamically generated
in response to user queries, which encode structured data and are displayed for human
use. Query result pages usually contain other types of information in addition to query
results, e.g., advertisements, navigation bar etc. The problem of extracting structured data
from query result pages is critical for web data integration applications, such as comparison
shopping, meta-search engines etc, and has been intensively studied. A number of approaches
have been proposed. As the structures of Web pages become more and more complex, the
existing approaches start to fail, and most of them do not remove irrelevant contents which
may a®ect the accuracy of data record extraction. We propose an automated approach for
Web data extraction. First, it makes use of visual features and query terms to identify data
sections and extracts data records in these sections. We also represent several content and
visual features of visual blocks in a data section, and use them to ¯lter out noisy blocks.
Second, it measures similarity between data items in di®erent data records based on their
visual and content features, and aligns them into di®erent groups so that the data in the
same group have the same semantics. The results of our experiments with a large set of
Web query result pages in di®erent domains show that our proposed approaches are highly
e®ective.

Talking about watching : using the video card game and wiki-web technology to engage IT students in developing observational skills.

Designers need to develop good observational skills in order to conduct user studies that reveal the subtleties of human interactions and adequately inform design activity. In this paper we describe a game format that we have used in concert with wiki-web technology, to engage our IT and Information Environments students in developing much sharper observational skills. The Video Card Game is a method of video analysis that is suited to design practitioners as well as to researchers. It uses the familiar format of a card game similar to "Happy Families,, to help students develop themes of interactions from watching video clips. Students then post their interaction themes on wiki-web pages, which allows the teaching team and other students to edit and comment on them. We found that the tangible (cards), game, role playing and sharing aspects of this method led to a much larger amount of interaction and discussion between student groups and between students and the teaching team, than we have achieved using our traditional teaching methods, while taking no more time on the part of the teaching staff. The quality of the resulting interaction themes indicates that this method fosters development of observational skills.In the paper we describe the motivations, method and results in full. We also describe the research context in which we collected the videotape data, and how this method relates to state of the art research methods in interaction design for ubiquitous computing technology.

Enhancing an Incremental Clustering Algorithm for Web Page Collections

With the size and state of the Internet today, a good quality approach to organizing this mass of information is of great importance. Clustering web pages into groups of similar documents is one approach, but relies heavily on good feature extraction and document representation as well as a good clustering approach and algorithm. Due to the changing nature of the Internet, resulting in a dynamic dataset, an incremental approach is preferred. In this work we propose an enhanced incremental clustering approach to develop a better clustering algorithm that can help to better organize the information available on the Internet in an incremental fashion. Experiments show that the enhanced algorithm outperforms the original histogram based algorithm by up to 7.5%.

Discovering interesting information with advances in web technology

The Web is a steadily evolving resource comprising much more than mere HTML pages. With its ever-growing data sources in a variety of formats, it provides great potential for knowledge discovery. In this article, we shed light on some interesting phenomena of the Web: the deep Web, which surfaces database records as Web pages; the Semantic Web, which de�nes meaningful data exchange formats; XML, which has established itself as a lingua franca for Web data exchange; and domain-speci�c markup languages, which are designed based on XML syntax with the goal of preserving semantics in targeted domains. We detail these four developments in Web technology, and explain how they can be used for data mining. Our goal is to show that all these areas can be as useful for knowledge discovery as the HTML-based part of the Web.

Retrieval of health advice on the web: AEHRC at ShARe/CLEF eHealth Evaluation Lab Task 3

This paper details the participation of the Australian e- Health Research Centre (AEHRC) in the ShARe/CLEF 2013 eHealth Evaluation Lab { Task 3. This task aims to evaluate the use of information retrieval (IR) systems to aid consumers (e.g. patients and their relatives) in seeking health advice on the Web. Our submissions to the ShARe/CLEF challenge are based on language models generated from the web corpus provided by the organisers. Our baseline system is a standard Dirichlet smoothed language model. We enhance the baseline by identifying and correcting spelling mistakes in queries, as well as expanding acronyms using AEHRC's Medtex medical text analysis platform. We then consider the readability and the authoritativeness of web pages to further enhance the quality of the document ranking. Measures of readability are integrated in the language models used for retrieval via prior probabilities. Prior probabilities are also used to encode authoritativeness information derived from a list of top-100 consumer health websites. Empirical results show that correcting spelling mistakes and expanding acronyms found in queries signi cantly improves the e ectiveness of the language model baseline. Readability priors seem to increase retrieval e ectiveness for graded relevance at early ranks (nDCG@5, but not precision), but no improvements are found at later ranks and when considering binary relevance. The authoritativeness prior does not appear to provide retrieval gains over the baseline: this is likely to be because of the small overlap between websites in the corpus and those in the top-100 consumer-health websites we acquired.

Parallel streaming signature EM-tree: A clustering algorithm for web scale applications

The proliferation of the web presents an unsolved problem of automatically analyzing billions of pages of natural language. We introduce a scalable algorithm that clusters hundreds of millions of web pages into hundreds of thousands of clusters. It does this on a single mid-range machine using efficient algorithms and compressed document representations. It is applied to two web-scale crawls covering tens of terabytes. ClueWeb09 and ClueWeb12 contain 500 and 733 million web pages and were clustered into 500,000 to 700,000 clusters. To the best of our knowledge, such fine grained clustering has not been previously demonstrated. Previous approaches clustered a sample that limits the maximum number of discoverable clusters. The proposed EM-tree algorithm uses the entire collection in clustering and produces several orders of magnitude more clusters than the existing algorithms. Fine grained clustering is necessary for meaningful clustering in massive collections where the number of distinct topics grows linearly with collection size. These fine-grained clusters show an improved cluster quality when assessed with two novel evaluations using ad hoc search relevance judgments and spam classifications for external validation. These evaluations solve the problem of assessing the quality of clusters where categorical labeling is unavailable and unfeasible.

Utility of web content blocks in content extraction

Currently we are facing an overburdening growth of the number of reliable information sources on the Internet. The quantity of information available to everyone via Internet is dramatically growing each year [15]. At the same time, temporal and cognitive resources of human users are not changing, therefore causing a phenomenon of information overload. World Wide Web is one of the main sources of information for decision makers (reference to my research). However our studies show that, at least in Poland, the decision makers see some important problems when turning to Internet as a source of decision information. One of the most common obstacles raised is distribution of relevant information among many sources, and therefore need to visit different Web sources in order to collect all important content and analyze it. A few research groups have recently turned to the problem of information extraction from the Web [13]. The most effort so far has been directed toward collecting data from dispersed databases accessible via web pages (related to as data extraction or information extraction from the Web) and towards understanding natural language texts by means of fact, entity, and association recognition (related to as information extraction). Data extraction efforts show some interesting results, however proper integration of web databases is still beyond us. Information extraction field has been recently very successful in retrieving information from natural language texts, however it is still lacking abilities to understand more complex information, requiring use of common sense knowledge, discourse analysis and disambiguation techniques.