HTML Tables Research Articles (Page 1)

TAPON-MT: A versatile framework for semantic labelling

There are rich data resources residing in available materials websites, and most of these data resources are shown in the form of HTML tables. However, it is difficult to distinguish the attributes and values because of the semi-structured feature of HTML tables. Therefore, identifying attributes in HTML tables is the key issue for the information acquisition. In this paper, based on sibling comparison, a method for materials knowledge extraction from HTML tables is proposed, which consists of three steps: acquiring sibling tables, identifying table pattern and extracting table data. We show how to use [Formula: see text]-measure to find the appropriate thresholds for matching of tables from materials websites when acquiring sibling tables. Further, we propose a strategy named FRFC (i.e. the First Row matching and First Column matching) to distinguish attributes and values, so that table pattern is identified. Moreover, the data from HTML tables is extracted based on their corresponding table patterns and mapped to a predefined schema, which will facilitate the population to materials ontology. The proposed approach is applicable to circumstances, where an attribute in the table may span multiple cells and matched attributes in sibling tables are more. We acquire desired accuracy ([Formula: see text]%) through using FRFC for identifying table pattern. The time about extraction may not increase significantly with increasing number of documents and cells in tables, so our approach is effective to process a large number of documents. A prototype named MTES is developed and demonstrates the effectiveness of our proposed approach.

Many websites contain very attractive and up to date geographical information. This information can be extracted, stored, analyzed and mapped using web harvesting techniques. Poorly organized data from websites are transformed with web harvesting into a more structured format, which can be stored in a database and analyzed. Almost 25% of web traffic is related to web harvesting, mostly while using search engines. This paper presents how to harvest geographic information from web documents using the free tool called the Beautiful Soup, one of the most commonly used Python libraries for pulling data from HTML and XML files. It is a relatively easy task to process one static HTML table. The more challenging task is to extract and save information from tables located in multiple and poorly organized websites. Legal and ethical aspects of web harvesting are discussed as well. The paper demonstrates two case studies. The first one shows how to extract various types of information about the Good Country Index from the multiple web pages, load it into one attribute table and map the results. The second case study shows how script tools and GIS can be used to extract information from one hundred thirty six websites about Nova Scotia wines. In a little more than three minutes a database containing one hundred and six liquor stores selling these wines is created. Then the availability and spatial distribution of various types of wines (by grape types, by wineries, and by liquor stores) are mapped and analyzed.

Automatic layout of tables is required in online applications because of the need to tailor the layout to the viewport width, choice of font, and dynamic content. However, if the table contains text, minimizing the height of the table for a fixed maximum width is NP-hard. Thus, more efficient heuristic algorithms are required. We evaluate the HTML table layout recommendation and find that while it generally produces quite compact layout it is brittle and can lead to quite uncompact layout. We present an alternate heuristic algorithm. It uses a greedy strategy that starts from the widest reasonable layout and repeatedly chooses to narrow the column for which narrowing leads to the least increase in table height. The algorithm is simple, fast enough to be used in online applications, and gives significantly more compact layout than is obtained with HTML’s recommended table layout algorithm.

The usage of PDA and mobile devices has dramatically increased recently. However, mobile devices and PDA devices have a limited screen size, which makes it frustrating to browse tabular data on mobile devices since users have to frequently scroll up and down to find the information of interest. This paper presents an efficient means to present HTML-based tables on mobile devices. Based on the column and row headers, the authors adapt a HTML-based Web table into two adaptive styles. The first style displays all information of a table into a single narrow page to avoid horizontal scrolling; and the second style distributes information to different sub-pages, each of which approximately occupies the whole mobile screen, and thus eliminates scrolling. The approach is empirically evaluated using a controlled experiment. The main conclusions derived from the empirical study are: (1) the adaptive layout styles improves the browsing efficiency for individual subjects as compared to HTML web page style, (2) the single narrow adaptive layout resulted in the improved browsing efficiency compared to the multi-page adaptive layout for one-dimensional HTML web page tables, and (3) the multi-page adaptive layout was more efficient than the single narrow adaptive layout for two-dimensional HTML tables.

Proteomic studies often produce sets of hundreds of proteins. Bioinformatic information for these large protein sets must be collected from multiple online resources. Protein Information Crawler (PIC) automatically bulk-collects such data from multiple databases and prediction servers, based on National Center for Biotechnology Information (NCBI) gi numbers or accession numbers, and summarizes them in a Microsoft Excel spreadsheet and/or HTML table. PIC greatly accelerates information procurement, helps to build customized protein information databases and drastically reduces manual database investigation in extensive proteomic studies. http://www.zoo.uni-heidelberg.de/mfa/PIC.

Content adaptation is an important technique for mobile devices. Existing content adaptation systems have been developed with specific adaptation goals. In this paper, we present an extensible content adaptation system, Xadaptor. We take a rule-based approach to facilitate extensible, systematic, and adaptive content adaptation. It integrates adaptation mechanisms for various content types and organizes them into the rule base. Rules are invoked based on the individual client information. We classify HTML page objects into structure, content, and pointer objects. Existing content adaptation techniques mainly focus on content objects and do not consider adaptation for structure and pointer objects. In Xadaptor, novel adaptation techniques for the structure object HTML table have been developed. We use fuzzy logic to model the adaptation quality and guide the adaptation decision. To demonstrate the feasibility of our approach, we have implemented a prototype system. Experimental studies show that Xadaptor is capable of on-the-fly content adaptation and is easily extensible

Dynamic queries are gaining popularity as a method for interactive information visualisation. Many implementations have been made on personal computers, and there is increasing interest in Web-based designs. While Java and Flash strategies have been developed, we believe that a Dynamic HTML implementation could help promote more widespread use. We implemented double-box range sliders with choropleth maps and scattergrams, which are two popular visualisations, using HTML layers and tables. This paper describes our methods for slider control, visual presentation, and displaying/updating results for these visualisations. Visual design issues innovations and performance enhancements were necessary to create viable designs.