An effective approach to verbose queries using a limited dependencies language model

Intuitively, any ‘bag of words’ approach in IR should benefit from taking term dependencies into account. Unfortunately, for years the results of exploiting such dependencies have been mixed or inconclusive. To improve the situation, this paper shows how the natural language properties of the target documents can be used to transform and enrich the term dependencies to more useful statistics. This is done in three steps. The term co-occurrence statistics of queries and documents are each represented by a Markov chain. The paper proves that such a chain is ergodic, and therefore its asymptotic behavior is unique, stationary, and independent of the initial state. Next, the stationary distribution is taken to model queries and documents, rather than their initial distributions. Finally, ranking is achieved following the customary language modeling paradigm. The main contribution of this paper is to argue why the asymptotic behavior of the document model is a better representation then just the document’s initial distribution. A secondary contribution is to investigate the practical application of this representation in case the queries become increasingly verbose. In the experiments (based on Lemur’s search engine substrate) the default query model was replaced by the stable distribution of the query. Just modeling the query this way already resulted in significant improvements over a standard language model baseline. The results were on a par or better than more sophisticated algorithms that use fine-tuned parameters or extensive training. Moreover, the more verbose the query, the more effective the approach seems to become.

Mammalian phylogeny

Living mammals can be divided into three subclasses (monotremes, marsupials and placentals) and within these, about 27 orders. Final resolution of the relationships between the orders is only now being achieved with the increased availability of deoxyribonucleic acid (DNA) sequences. Highlights include the deep division of placental mammals into African (Afrotheria), South American (Xenarthra) and northern hemisphere (Boreoeutheria) super-orders, and the finding that the once considered primitive ‘Insectivora’ and ‘Edentata’ clades, in fact, have members distributed widely among these super-orders. Another surprise finding from DNA studies has been that whale origins lie among the even-toed ungulates (Artiodactyla). Our order, Primates is most closely related to the flying lemurs and next, the tree shrews. With the mammal phylogeny becoming well resolved, it is increasingly being used as a framework for inferring evolutionary and ecological processes, such as adaptive radiation.