Onebox: Free-Text Interfaces as an Alternative to Complex Web Forms

This paper investigates the problem of translating free-text\ud queries into key-value pairs as an alternative means for searching `behind' web forms. We introduce a novel specication language for specifying free-text interfaces, and report the results of a user study where we evaluated our prototype in a travel planner scenario. Our results show that users prefer this free-text interface over the original web form and that they are about 9% faster on average at completing their search tasks

Self-adaptive Based Model for Ambiguity Resolution of The Linked Data Query for Big Data Analytics

Integration of heterogeneous data sources is a crucial step in big data analytics, although it creates ambiguity issues during mapping between the sources due to the variation in the query terms, data structure and granularity conflicts. However, there are limited researches on effective big data integration to address the ambiguity issue for big data analytics. This paper introduces a self-adaptive model for big data integration by exploiting the data structure during querying in order to mitigate and resolve ambiguities. An assessment of a preliminary work on the Geography and Quran dataset is reported to illustrate the feasibility of the proposed model that motivates future work such as solving complex query

Visual Query Formulation for Linked Open Data: The Norwegian Entity Registry Case

The cloud of Linked Open Data is steadily growing, yet it remains largelyinaccessible to the general public, due to the technical barrier posed bythe requirement to know a formal query language such as SPARQL. Inthis article, we present a new approach for visual query formulation towardarbitrary SPARQL endpoints, and we show a working prototype developedto improve the accessibility to Linked Open Data sources for non-computerexperts. We show how the prototype can be employed to simplify access togovernmental Linked Open Data with a case study from the Norwegian EntityRegistry

Knowledge Rich Natural Language Queries over Structured Biological Databases

Increasingly, keyword, natural language and NoSQL queries are being used for information retrieval from traditional as well as non-traditional databases such as web, document, image, GIS, legal, and health databases. While their popularity are undeniable for obvious reasons, their engineering is far from simple. In most part, semantics and intent preserving mapping of a well understood natural language query expressed over a structured database schema to a structured query language is still a difficult task, and research to tame the complexity is intense. In this paper, we propose a multi-level knowledge-based middleware to facilitate such mappings that separate the conceptual level from the physical level. We augment these multi-level abstractions with a concept reasoner and a query strategy engine to dynamically link arbitrary natural language querying to well defined structured queries. We demonstrate the feasibility of our approach by presenting a Datalog based prototype system, called BioSmart, that can compute responses to arbitrary natural language queries over arbitrary databases once a syntactic classification of the natural language query is made

BESDUI: A Benchmark for End-User Structured Data User Interfaces

The Semantic Web Community has invested significant research efforts in developing systems for Semantic Web search and exploration. But while it has been easy to assess the systems’ computational efficiency, it has been much harder to assess how well different semantic systems’ user interfaces help their users. In this article, we propose and demonstrate the use of a benchmark for evaluating such user interfaces, similar to the TREC benchmark for evaluating traditional search engines. Our benchmark includes a set of typical user tasks and a well-defined procedure for assigning a measure of performance on those tasks to a semantic system. We demonstrate its application to two such system, Virtuoso and Rhizomer. We intend for this work to initiate a community conversation that will lead to a generally accepted framework for comparing systems and for measuring, and thus encouraging, progress towards better semantic search and exploration tools

Qualifying Ontology-Based Visual Query Formulation

Abstract. This paper elaborates on ontology-based end-user visual query formulation, particularly for users who otherwise cannot/do not desire to use formal textual query languages to retrieve data due to the lack of technical knowledge and skills. Then, it provides a set of quality attributes and features, primarily elicited via a series of industrial end-user workshops and user studies carried out in the course of an industrial EU project, to guide the design and development of successor visual query systems

Responsive and Flexible Controlled Natural Language Authoring with Zipper-based Transformations

International audienceControlled natural languages (CNL) have the benefits to combine the readability of natural languages, and the accuracy of formal languages. They have been used to help users express facts, rules or queries. While generally easy to read, CNLs remain difficult to write because of the constrained syntax. A common solution is a grammar-based auto-completion mechanism to suggest the next possible words in a sentence. However, this solution has two limitations: (a) partial sentences may have no semantics, which prevents giving intermediate results or feedback, and (b) the suggestion is often limited to adding words at the end of the sentence. We propose a more responsive and flexible CNL authoring by designing it as a sequence of sentence transformations. Responsiveness is obtained by having a complete, and hence interpretable, sentence at each time. Flexibility is obtained by allowing insertion and deletion on any part of the sentence. Technically, this is realized by working directly on the abstract syntax, rather than on the concrete syntax , and by using Huet's zippers to manage the focus on a query part, the equivalent of the text cursor of a word processor

QUESTION ANSWERING SYSTEMS

Sustavi pitanja i odgovora su način pretraživanja informacija koji odgovara na pitanje postavljeno prirodnim jezikom. Sastoje se od triju glavnih komponenata: klasifikacija pitanja, pronalaženja informacija i izvlačenja odgovora. Uvođenjem velikih zajedničkih procjena, kao što je TREC konferencija, stvorene su snažne interesne zajednice i ubrzan napredak u istraživanju sustava pitanja i odgovora. U radu su prikazane domene problema odgovaranja na pitanja. Prikazan je povijesni razvoj sustava pitanja i odgovora od jednostavnijih, koji su bili usko specijalizirani, do današnjih, puno složenijih i kvalitetnijih sustava koji su sposobni dati nam kratke i sažete odgovore na pitanja iz raznih domena. Analizirani su sustavi prema namjeni. Dat je pregled dosadašnjih istraživanja o sustavima pitanja i odgovora. Definirana je opća arhitektura sustava pitanja i odgovora te analizirani aktualni pristupi u svakoj fazi arhitekture. Sustavi pitanja i odgovora još uvijek su u fazi razvoja i eksperimentiranja. Zaključeno je kako još uvijek najveći problem sustava pitanja i odgovora predstavlja odabir najtočnijeg i najsažetijeg odgovora s kojim će korisnik biti zadovoljan.The question answering systems are a way of information retrieval that responds to the question asked in natural language. They consist of three main components : question classification, information retrieval and response extraction. The implementation of large-scale joint assessments such as TREC conference, has created a powerful interest community and accelerated the progress in the study of question answering systems. This paper presents the problem domains in answering questions. It reviews the historical development of the question answering systems, from the simplest highly specialized ones to the present more sophisticated and higer quality systems that are able to give us short and concise answers to questions belonging to a variety of domains. The systems are analyzed according to the purpose. The paper provides an overview of previous research on question answering systems. It defines the general architecture of question answering systems and analyzes current approaches to every phase of architecture. The question answering systems are still under development and experimentation. In conclusion, the selection of the most accurate and the most concise response that will satisfy the user, still remains the largest problem in question answering systems

Semantic Queries Expedite MedDRA Terms Selection Thanks to a Dedicated User Interface: A Pilot Study on Five Medical Conditions

Background: Searching into the MedDRA terminology is usually limited to a hierarchical search, and/or a string search. Our objective was to compare user performances when using a new kind of user interface enabling semantic queries versus classical methods, and evaluating term selection improvement in MedDRA.Methods: We implemented a forms-based web interface: OntoADR Query Tools (OQT). It relies on OntoADR, a formal resource describing MedDRA terms using SNOMED CT concepts and corresponding semantic relations, enabling terminological reasoning. We then compared time spent on five examples of medical conditions using OQT or the MedDRA web-based browser (MWB), and precision and recall of the term selection.Results: OntoADR Query Tools allows the user to search in MedDRA: One may enter search criteria by selecting one semantic property from a dropdown list and one or more SNOMED CT concepts related to the range of the chosen property. The user is assisted in building his query: he can add criteria and combine them. Then, the interface displays the set of MedDRA terms matching the query. Meanwhile, on average, the time spent on OQT (about 4 min 30 s) is significantly lower (−35%; p < 0.001) than time spent on MWB (about 7 min). The results of the System Usability Scale (SUS) gave a score of 62.19 for OQT (rated as good). We also demonstrated increased precision (+27%; p = 0.01) and recall (+34%; p = 0.02). Computed “performance” (correct terms found per minute) is more than three times better with OQT than with MWB.Discussion: This pilot study establishes the feasibility of our approach based on our initial assumption: performing MedDRA queries on the five selected medical conditions, using terminological reasoning, expedites term selection, and improves search capabilities for pharmacovigilance end users. Evaluation with a larger number of users and medical conditions are required in order to establish if OQT is appropriate for the needs of different user profiles, and to check if conclusions can be extended to other kinds of medical conditions. The application is currently limited by the non-exhaustive coverage of MedDRA by OntoADR, but nevertheless shows good performance which encourages continuing in the same direction