Extracting Hierarchies of Search Tasks & Subtasks via a Bayesian Nonparametric Approach

A significant amount of search queries originate from some real world information need or tasks. In order to improve the search experience of the end users, it is important to have accurate representations of tasks. As a result, significant amount of research has been devoted to extracting proper representations of tasks in order to enable search systems to help users complete their tasks, as well as providing the end user with better query suggestions, for better recommendations, for satisfaction prediction, and for improved personalization in terms of tasks. Most existing task extraction methodologies focus on representing tasks as flat structures. However, tasks often tend to have multiple subtasks associated with them and a more naturalistic representation of tasks would be in terms of a hierarchy, where each task can be composed of multiple (sub)tasks. To this end, we propose an efficient Bayesian nonparametric model for extracting hierarchies of such tasks \& subtasks. We evaluate our method based on real world query log data both through quantitative and crowdsourced experiments and highlight the importance of considering task/subtask hierarchies.Comment: 10 pages. Accepted at SIGIR 2017 as a full pape

A Bayesian phylogenetic hidden Markov model for B cell receptor sequence analysis.

The human body generates a diverse set of high affinity antibodies, the soluble form of B cell receptors (BCRs), that bind to and neutralize invading pathogens. The natural development of BCRs must be understood in order to design vaccines for highly mutable pathogens such as influenza and HIV. BCR diversity is induced by naturally occurring combinatorial "V(D)J" rearrangement, mutation, and selection processes. Most current methods for BCR sequence analysis focus on separately modeling the above processes. Statistical phylogenetic methods are often used to model the mutational dynamics of BCR sequence data, but these techniques do not consider all the complexities associated with B cell diversification such as the V(D)J rearrangement process. In particular, standard phylogenetic approaches assume the DNA bases of the progenitor (or "naive") sequence arise independently and according to the same distribution, ignoring the complexities of V(D)J rearrangement. In this paper, we introduce a novel approach to Bayesian phylogenetic inference for BCR sequences that is based on a phylogenetic hidden Markov model (phylo-HMM). This technique not only integrates a naive rearrangement model with a phylogenetic model for BCR sequence evolution but also naturally accounts for uncertainty in all unobserved variables, including the phylogenetic tree, via posterior distribution sampling

Species Limits and Phylogeography of North American Cricket Frogs (Acris: Hylidae)

Cricket frogs are widely distributed across the eastern United States and two species, the northern cricket frog (Acris crepitans) and the southern cricket frog (A. gryllus) are currently recognized. We generated a phylogenetic hypothesis for Acris using fragments of nuclear and mitochondrial genes in separate and combined phylogenetic analyses. We also used distance methods and fixation indices to evaluate species limits within the genus and the validity of currently recognized subspecies of A. crepitans. The distributions of existing A. crepitans subspecies, defined by morphology and call types, do not match the distributions of evolutionary lineages recovered using our genetic data. We discuss a scenario of call evolution to explain this disparity. We also recovered distinct phylogeographic groups within A. crepitans and A. gryllus that are congruent with other codistributed taxa. Under a lineage-based species concept, we recognize Acris blanchardi as a distinct species. The importance of this revised taxonomy is discussed in light of the dramatic declines in A. blanchardi across the northern and western portions of its range

Inducing Compact but Accurate Tree-Substitution Grammars

Tree substitution grammars (TSGs) are a compelling alternative to context-free grammars for modelling syntax. However, many popular techniques for estimating weighted TSGs (under the moniker of Data Oriented Parsing) suffer from the problems of inconsistency and over-fitting. We present a theoretically principled model which solves these problems using a Bayesian non-parametric formulation. Our model learns compact and simple grammars, uncovering latent linguistic structures (e.g., verb subcategorisation), and in doing so far out-performs a standard PCFG.

Bayesian Inference for PCFGs via Markov Chain Monte Carlo

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Deep mtDNA divergences indicate cryptic species in a fig-pollinating wasp

Background: Figs and fig-pollinating wasps are obligate mutualists that have coevolved for ca 90 million years. They have radiated together, but do not show strict cospeciation. In particular, it is now clear that many fig species host two wasp species, so there is more wasp speciation than fig speciation. However, little is known about how fig wasps speciate. Results: We studied variation in 71 fig-pollinating wasps from across the large geographic range of Ficus rubiginosa in Australia. All wasps sampled belong to one morphological species (Pleistodontes imperialis), but we found four deep mtDNA clades that differed from each other by 9–17% nucleotides. As these genetic distances exceed those normally found within species and overlap those (10–26%) found between morphologically distinct Pleistodontes species, they strongly suggest cryptic fig wasp species. mtDNA clade diversity declines from all four present in Northern Queensland to just one in Sydney, near the southern range limit. However, at most sites multiple clades coexist and can be found in the same tree or even the same fig fruit and there is no evidence for parallel sub-division of the host fig species. Both mtDNA data and sequences from two nuclear genes support the monophyly of the "P. imperialis complex" relative to other Pleistodontes species, suggesting that fig wasp divergence has occurred without any host plant shift. Wasps in clade 3 were infected by a single strain (W1) of Wolbachia bacteria, while those in other clades carried a double infection (W2+W3) of two other strains. Conclusion: Our study indicates that cryptic fig-pollinating wasp species have developed on a single host plant species, without the involvement of host plant shifts, or parallel host plant divergence. Despite extensive evidence for coevolution between figs and fig wasps, wasp speciation may not always be linked strongly with fig speciation