Crowd-sourced collection of task-oriented human-human dialogues in a multi-domain scenario

There is a lack of high-quality corpora for the purposes of trainingtask-oriented, end-to-end dialogue systems. This paper describes a dialogue col-lection process which used crowd-sourcing and a Wizard-of-Oz set-up to collectwritten human-human dialogues for a task-oriented, multi-domain scenario. Thecontext is a tourism agency, where users try to select the more desired hotel,restaurant, museum or shop. To respond to users, wizards were assisted by an ex-ploratory system supporting Preference-enriched Faceted Search. An importantaspect was the translation of user intent to a number of actions (hard or soft-constraints) by wizards. The main goal was to collect dialogues as realistic aspossible between a user and an operator, suitable for training end-to-end dialoguesystems. This work describes the experiences made, the options and the deci-sions taken to minimize the human effort and budget, along with the tools usedand developed, and describes in detail the resulting dialogue collection

How Many and What Types of SPARQL Queries can be Answered through Zero-Knowledge Link Traversal?

The current de-facto way to query the Web of Data is through the SPARQL protocol, where a client sends queries to a server through a SPARQL endpoint. Contrary to an HTTP server, providing and maintaining a robust and reliable endpoint requires a significant effort that not all publishers are willing or able to make. An alternative query evaluation method is through link traversal, where a query is answered by dereferencing online web resources (URIs) at real time. While several approaches for such a lookup-based query evaluation method have been proposed, there exists no analysis of the types (patterns) of queries that can be directly answered on the live Web, without accessing local or remote endpoints and without a-priori knowledge of available data sources. In this paper, we first provide a method for checking if a SPARQL query (to be evaluated on a SPARQL endpoint) can be answered through zero-knowledge link traversal (without accessing the endpoint), and analyse a large corpus of real SPARQL query logs for finding the frequency and distribution of answerable and non-answerable query patterns. Subsequently, we provide an algorithm for transforming answerable queries to SPARQL-LD queries that bypass the endpoints. We report experimental results about the efficiency of the transformed queries and discuss the benefits and the limitations of this query evaluation method.Comment: Preprint of paper accepted for publication in the 34th ACM/SIGAPP Symposium On Applied Computing (SAC 2019

Understanding constraint expressions in large conceptual schemas by automatic filtering

Human understanding of constraint expressions (also called schema rules) in large conceptual schemas is very di cult. This is due to the fact that the elements (entity types, attributes, relationship types) involved in an expression are de ned in di fferent places in the schema, which may be very distant from each other and embedded in an intricate web of irrelevant elements. The problem is insignifi cant when the conceptual schema is small, but very signi cant when it is large. In this paper we describe a novel method that, given a set of constraint expressions and a large conceptual schema, automatically filters the conceptual schema, obtaining a smaller one that contains the elements of interest for the understanding of the expressions. We also show the application of the method to the important case of understanding the specication of event types, whose constraint expressions consists of a set of pre and postconditions. We have evaluated the method by means of its application to a set of large conceptual schemas. The results show that the method is eff ective and e cient. We deal with conceptual schemas in UML/OCL, but the method can be adapted to other languages.Peer ReviewedPreprin

Knowledge Driven Intelligent Survey Systems for Linguists

This work was supported the EU Marie Curie K-Drive project (286348).Postprin

Improving pulse crops as a source of protein, starch and micronutrients

Pulse crops have been known for a long time to have beneficial nutritional profiles for human diets but have been neglected in terms of cultivation, consumption and scientific research in many parts of the world. Broad dietary shifts will be required if anthropogenic climate change is to be mitigated in the future, and pulse crops should be an important component of this change by providing an environmentally sustainable source of protein, resistant starch and micronutrients. Further enhancement of the nutritional composition of pulse crops could benefit human health, helping to alleviate micronutrient deficiencies and reduce risk of chronic diseases such as type 2 diabetes. This paper reviews current knowledge regarding the nutritional content of pea (Pisum sativum L.) and faba bean (Vicia faba L.), two major UK pulse crops, and discusses the potential for their genetic improvement

Towards a Generalized Interaction Scheme for Information Access

We introduce the formal framework of a generalized interaction scheme for information access between users and information sources. Within this framework we describe an interaction manager which supports more complex interaction schemes than those that are supported by existing systems, including: query by example, answer enlargement/reduction, query relaxation/restriction, index relaxation/contraction, "relevance" feedback, and adaptation facilities. We give the foundations of this interaction manager from a mathematical point of view, in terms of an abstract view of an information source

Query Evaluation in Peer-to-Peer Networks of Taxonomy-Based Sources

We consider the problem of query evaluation in Peer-to-Peer (P2P) systems that support semantic-based retrieval services. We confine ourselves to the case where the peers employ taxonomies for describing the contents of the objects, and articulations, i.e. inter-taxonomy mappings, for bridging the inevitable naming, granularity and contextual heterogeneities that may exist between the taxonomies of the sources