Composite repetition-aware data structures

In highly repetitive strings, like collections of genomes from the same species, distinct measures of repetition all grow sublinearly in the length of the text, and indexes targeted to such strings typically depend only on one of these measures. We describe two data structures whose size depends on multiple measures of repetition at once, and that provide competitive tradeoffs between the time for counting and reporting all the exact occurrences of a pattern, and the space taken by the structure. The key component of our constructions is the run-length encoded BWT (RLBWT), which takes space proportional to the number of BWT runs: rather than augmenting RLBWT with suffix array samples, we combine it with data structures from LZ77 indexes, which take space proportional to the number of LZ77 factors, and with the compact directed acyclic word graph (CDAWG), which takes space proportional to the number of extensions of maximal repeats. The combination of CDAWG and RLBWT enables also a new representation of the suffix tree, whose size depends again on the number of extensions of maximal repeats, and that is powerful enough to support matching statistics and constant-space traversal.Comment: (the name of the third co-author was inadvertently omitted from previous version

Computing LZ77 in Run-Compressed Space

In this paper, we show that the LZ77 factorization of a text T {\in\Sigma^n} can be computed in O(R log n) bits of working space and O(n log R) time, R being the number of runs in the Burrows-Wheeler transform of T reversed. For extremely repetitive inputs, the working space can be as low as O(log n) bits: exponentially smaller than the text itself. As a direct consequence of our result, we show that a class of repetition-aware self-indexes based on a combination of run-length encoded BWT and LZ77 can be built in asymptotically optimal O(R + z) words of working space, z being the size of the LZ77 parsing

A Psychogenetic Algorithm for Behavioral Sequence Learning

This work presents an original algorithmic model of some essential features of psychogenetic theory, as was proposed by J.Piaget. Specifically, we modeled some elements of cognitive structure learning in children from 0 to 4 months of life. We are in fact convinced that the study of well-established cognitive models of human learning can suggest new, interesting approaches to problem so far not satisfactorily solved in the field of machine learning. Further, we discussed the possible parallels between our model and subsymbolic machine learning and neuroscience. The model was implemented and tested in some simple experimental settings, with reference to the task of learning sensorimotor sequences

Moving Toward Non-transcription Based Discourse Analysis in Stable and Progressive Aphasia

Measurement of communication ability at the discourse level holds promise for predicting how well persons with stable (e.g., stroke-induced), or progressive aphasia navigate everyday communicative interactions. However, barriers to the clinical utilization of discourse measures have persisted. Recent advancements in the standardization of elicitation protocols and the existence of large databases for development of normative references have begun to address some of these barriers. Still, time remains a consistently reported barrier by clinicians. Non-transcription based discourse measurement would reduce the time required for discourse analysis, making clinical utilization a reality. The purpose of this article is to present evidence regarding discourse measures (main concept analysis, core lexicon, and derived efficiency scores) that are well suited to non-transcription based analysis. Combined with previous research, our results suggest that these measures are sensitive to changes following stroke or neurodegenerative disease. Given the evidence, further research specifically assessing the reliability of these measures in clinical implementation is warranted

Fast Label Extraction in the CDAWG

The compact directed acyclic word graph (CDAWG) of a string $T$ of length $n$ takes space proportional just to the number $e$ of right extensions of the maximal repeats of $T$, and it is thus an appealing index for highly repetitive datasets, like collections of genomes from similar species, in which $e$ grows significantly more slowly than $n$. We reduce from $O(m\log{\log{n}})$ to $O(m)$ the time needed to count the number of occurrences of a pattern of length $m$, using an existing data structure that takes an amount of space proportional to the size of the CDAWG. This implies a reduction from $O(m\log{\log{n}}+\mathtt{occ})$ to $O(m+\mathtt{occ})$ in the time needed to locate all the $\mathtt{occ}$ occurrences of the pattern. We also reduce from $O(k\log{\log{n}})$ to $O(k)$ the time needed to read the $k$ characters of the label of an edge of the suffix tree of $T$, and we reduce from $O(m\log{\log{n}})$ to $O(m)$ the time needed to compute the matching statistics between a query of length $m$ and $T$, using an existing representation of the suffix tree based on the CDAWG. All such improvements derive from extracting the label of a vertex or of an arc of the CDAWG using a straight-line program induced by the reversed CDAWG.Comment: 16 pages, 1 figure. In proceedings of the 24th International Symposium on String Processing and Information Retrieval (SPIRE 2017). arXiv admin note: text overlap with arXiv:1705.0864

Narrating the archive and archiving narrative: the electronic book and the logic of the index

The creation of my hypermedia work Index of Love, which narrates a love story as an archive of moments, images and objects recollected, also articulated for me the potential of the book as electronic text. The book has always existed as both narrative and archive. Tables of contents and indexes allow the book to function simultaneously as linear narrative and non-linear, searchable database. The book therefore has more in common with the so-called 'new media' of the 21st century than it does with the dominant 20th century media of film, video and audiotape, whose logic and mode of distribution are resolutely linear. My thesis is that the non-linear logic of new media brings to the fore an aspect of the book - the index - whose potential for the production of narrative is only just beginning to be explored. When a reader/user accesses an electronic work, such as a website, via its menu, they simultaneously experience it as narrative and archive. The narrative journey taken is created through the menu choices made. Within the electronic book, therefore, the index (or menu) has the potential to function as more than just an analytical or navigational tool. It has the potential to become a creative, structuring device. This opens up new possibilities for the book, particularly as, in its paper based form, the book indexes factual work, but not fiction. In the electronic book, however, the index offers as rich a potential for fictional narratives as it does for factual volumes. [ABSTRACT FROM AUTHOR