Text segmentation in unconstrained hand-drawings in whiteboard photos

In this paper we present a robust method to detect handwritten text from unconstrained drawings on normal whiteboards. Unlike printed text on documents, free form handwritten text has no pattern in terms of size, orientation and font and it is often mixed with other drawings such as lines and shapes. Unlike handwritings on paper, handwritings on a normal whiteboard cannot be scanned so the detection has to be based on photos. Our work traces straight edges on photos of the whiteboard and builds graph representation of connected components. We use geometric properties such as edge density, graph density, aspect ratio and neighborhood similarity to differentiate handwritten text from other drawings. The experiment results show that our method achieves satisfactory precision and recall. Furthermore, the method is robust and efficient enough to be deployed in a mobile device. This is an important enabler of business applications that support whiteboard-centric visual meetings in enterprise scenarios. © 2012 IEEE.

Patient safety and the RCA: A document analysis

This research examined the function of Queensland Health's Root Cause Analysis (RCA) to improve patient safety through an investigation of patient harm events where permanent harm and preventable death, Severity Assessment Code 1, were the outcome of healthcare. Unedited and highly legislated RCAs from across Queensland Health public hospitals from 2009, 2010 and 2011 comprised the data. A document analysis revealed the RCAs opposed organisational policy and dominant theoretical directives. If we accept the prevailing assumption that patient harm is a systemic issue, then the RCA is failing to address harm events in healthcare.

Document timespan normalisation and understanding temporality for clinical records search

Previous qualitative research has highlighted that temporality plays an important role in relevance for clinical records search. In this study, an investigation is undertaken to determine the effect that the timespan of events within a patient record has on relevance in a retrieval scenario. In addition, based on the standard practise of document length normalisation, a document timespan normalisation model that specifically accounts for timespans is proposed. Initial analysis revealed that in general relevant patient records tended to cover a longer timespan of events than non-relevant patient records. However, an empirical evaluation using the TREC Medical Records track supports the opposite view that shorter documents (in terms of timespan) are better for retrieval. These findings highlight that the role of temporality in relevance is complex and how to effectively deal with temporality within a retrieval scenario remains an open question.

Semi-supervised document clustering via loci

Document clustering is one of the prominent methods for mining important information from the vast amount of data available on the web. However, document clustering generally suffers from the curse of dimensionality. Providentially in high dimensional space, data points tend to be more concentrated in some areas of clusters. We take advantage of this phenomenon by introducing a novel concept of dynamic cluster representation named as loci. Clusters’ loci are efficiently calculated using documents’ ranking scores generated from a search engine. We propose a fast loci-based semi-supervised document clustering algorithm that uses clusters’ loci instead of conventional centroids for assigning documents to clusters. Empirical analysis on real-world datasets shows that the proposed method produces cluster solutions with promising quality and is substantially faster than several benchmarked centroid-based semi-supervised document clustering methods.

CCD: Connected Component Descriptor for Robust Mosaicing of Camera-Captured Document Images

We propose a robust method for mosaicing of document images using features derived from connected components. Each connected component is described using the Angular Radial Tran. form (ART). To ensure geometric consistency during feature matching, the ART coefficients of a connected component are augmented with those of its two nearest neighbors. The proposed method addresses two critical issues often encountered in correspondence matching: (i) The stability of features and (ii) Robustness against false matches due to the multiple instances of characters in a document image. The use of connected components guarantees a stable localization across images. The augmented features ensure a successful correspondence matching even in the presence of multiple similar regions within the page. We illustrate the effectiveness of the proposed method on camera captured document images exhibiting large variations in viewpoint, illumination and scale.

Scalable document hashing and retrieval

This thesis studies document signatures, which are small representations of documents and other objects that can be stored compactly and compared for similarity. This research finds that document signatures can be effectively and efficiently used to both search and understand relationships between documents in large collections, scalable enough to search a billion documents in a fraction of a second. Deliverables arising from the research include an investigation of the representational capacity of document signatures, the publication of an open-source signature search platform and an approach for scaling signature retrieval to operate efficiently on collections containing hundreds of millions of documents.

The potential for consumer segmentation in the Finnish housing market

This article examines whether cluster analysis can be used to identify groups of Finnish residents with similar housing preferences. Because homebuilders in Finland have been providing relatively homogeneous products to an increasingly diverse population, current housing may not represent the occupiers' preferences so a segmentation approach relying on socioeconomic characteristics and expressed preferences may not be sufficient. We use data collected via questionnaire in a principal component analysis followed by a hierarchical cluster analysis to determine whether different combinations of housing attributes are important to groups of residents. We can identify four clusters of housing residents based on important characteristics when looking for a house. The clusters describe Finnish people in different phases of the life cycle and with different preferences based on their recreational activities and financial expenditures. Mass customization of housing could be used to better appeal to these different clusters of consumers who share similar preferences, increasing consumer satisfaction and improving profitability.

Document collage of correspondence and press materials; Juedische Winterhilfe der Juedische Gemeinde; Berlin Jewish Institutions

"die Firmen-Werbung setztein"

Reproduction of document collage; Juedische Winterhilfe der Juedische Gemeinde; Berlin Jewish Institutions

"auch 8000 Angestellte wurden geworben"

Parents as co-researchers at home: Using an observational method to document young children’s use of technology

This paper discusses the use of observational video recordings to document young children’s use of technology in their homes. Although observational research practices have been used for decades, often with video-based techniques, the participant group in this study (i.e., very young children) and the setting (i.e., private homes), provide a rich space for exploring the benefits and limitations of qualitative observation. The data gathered in this study point to a number of key decisions and issues that researchers must face in designing observational research, particularly where non-researchers (in this case, parents) act as surrogates for the researcher at the data collection stage. The involvement of parents and children as research videographers in the home resulted in very rich and detailed data about children’s use of technology in their daily lives. However, limitations noted in the dataset (e.g., image quality) provide important guidance for researchers developing projects using similar methods in future. The paper provides recommendations for future observational designs in similar settings and/or with similar participant groups.

Mining topical relevant patterns for multi-document summarization

Multi-document summarization addressing the problem of information overload has been widely utilized in the various real-world applications. Most of existing approaches adopt term-based representation for documents which limit the performance of multi-document summarization systems. In this paper, we proposed a novel pattern-based topic model (PBTMSum) for the task of the multi-document summarization. PBTMSum combining pattern mining techniques with LDA topic modelling could generate discriminative and semantic rich representations for topics and documents so that the most representative and non-redundant sentences can be selected to form a succinct and informative summary. Extensive experiments are conducted on the data of document understanding conference (DUC) 2007. The results prove the effectiveness and efficiency of our proposed approach.

Compound heterozygous mutations in RIPPLY2 associated with vertebral segmentation defects

Segmentation defects of the vertebrae (SDV) are caused by aberrant somite formation during embryogenesis and result in irregular formation of the vertebrae and ribs. The Notch signal transduction pathway plays a critical role in somite formation and patterning in model vertebrates. In humans, mutations in several genes involved in the Notch pathway are associated with SDV, with both autosomal recessive (MESP2, DLL3, LFNG, HES7) and autosomal dominant (TBX6) inheritance. However, many individuals with SDV do not carry mutations in these genes. Using whole-exome capture and massive parallel sequencing, we identified compound heterozygous mutations in RIPPLY2 in two brothers with multiple regional SDV, with appropriate familial segregation. One novel mutation (c.A238T:p.Arg80*) introduces a premature stop codon. In transiently transfected C2C12 mouse myoblasts, the RIPPLY2 mutant protein demonstrated impaired transcriptional repression activity compared with wild-type RIPPLY2 despite similar levels of expression. The other mutation (c.240-4T>G), with minor allele frequency <0.002, lies in the highly conserved splice site consensus sequence 5' to the terminal exon. Ripply2 has a well-established role in somitogenesis and vertebral column formation, interacting at both gene and protein levels with SDV-associated Mesp2 and Tbx6. We conclude that compound heterozygous mutations in RIPPLY2 are associated with SDV, a new gene for this condition. © The Author 2014.