Is question answering fit for the Semantic Web? A survey

With the recent rapid growth of the Semantic Web (SW), the processes of searching and querying content that is both massive in scale and heterogeneous have become increasingly challenging. User-friendly interfaces, which can support end users in querying and exploring this novel and diverse, structured information space, are needed to make the vision of the SW a reality. We present a survey on ontology-based Question Answering (QA), which has emerged in recent years to exploit the opportunities offered by structured semantic information on the Web. First, we provide a comprehensive perspective by analyzing the general background and history of the QA research field, from influential works from the artificial intelligence and database communities developed in the 70s and later decades, through open domain QA stimulated by the QA track in TREC since 1999, to the latest commercial semantic QA solutions, before tacking the current state of the art in open userfriendly interfaces for the SW. Second, we examine the potential of this technology to go beyond the current state of the art to support end-users in reusing and querying the SW content. We conclude our review with an outlook for this novel research area, focusing in particular on the R&D directions that need to be pursued to realize the goal of efficient and competent retrieval and integration of answers from large scale, heterogeneous, and continuously evolving semantic sources

MT techniques in a retrieval system of semantically enriched patents

This paper focuses on how automatic translation techniques integrated in a patent retrieval system increase its capabilities and make possible extended features and functionalities. We describe 1) a novel methodology for natural language to SPARQL translation based on a grammar– ontology interoperability automation and a query grammar for the patents domain; 2) a devised strategy for statisticalbased translation of patents that allows to transfer semantic annotations to the target language; 3) a built-in knowledge representation infrastructure that uses multilingual semantic annotations; and 4) an online application that offers a multilingual search interface over structural knowledge databases (domain ontologies) and multilingual documents (biomedical patents) that have been automatically translated.Peer ReviewedPostprint (published version

NLSC: Unrestricted Natural Language-based Service Composition through Sentence Embeddings

Current approaches for service composition (assemblies of atomic services) require developers to use: (a) domain-specific semantics to formalize services that restrict the vocabulary for their descriptions, and (b) translation mechanisms for service retrieval to convert unstructured user requests to strongly-typed semantic representations. In our work, we argue that effort to developing service descriptions, request translations, and matching mechanisms could be reduced using unrestricted natural language; allowing both: (1) end-users to intuitively express their needs using natural language, and (2) service developers to develop services without relying on syntactic/semantic description languages. Although there are some natural language-based service composition approaches, they restrict service retrieval to syntactic/semantic matching. With recent developments in Machine learning and Natural Language Processing, we motivate the use of Sentence Embeddings by leveraging richer semantic representations of sentences for service description, matching and retrieval. Experimental results show that service composition development effort may be reduced by more than 44\% while keeping a high precision/recall when matching high-level user requests with low-level service method invocations.Comment: This paper will appear on SCC'19 (IEEE International Conference on Services Computing) on July 1

Interchanging lexical resources on the Semantic Web

Lexica and terminology databases play a vital role in many NLP applications, but currently most such resources are published in application-specific formats, or with custom access interfaces, leading to the problem that much of this data is in ‘‘data silos’’ and hence difficult to access. The Semantic Web and in particular the Linked Data initiative provide effective solutions to this problem, as well as possibilities for data reuse by inter-lexicon linking, and incorporation of data categories by dereferencable URIs. The Semantic Web focuses on the use of ontologies to describe semantics on the Web, but currently there is no standard for providing complex lexical information for such ontologies and for describing the relationship between the lexicon and the ontology. We present our model, lemon, which aims to address these gap

Using an ontology for guiding natural language interaction with knowledge based systems

Des dels anys 80, els sistemes basats en el coneixement, programes que utilitzen una gran quantitat de informació per modelar situacions i resoldre problemes, han adquirit gran importància en el camp industrial, financer i científic. La complexitat d'aquests sistemes fa que el seu ús presenti més dificultats que altres aplicacions informàtiques. La comunicació entre els sistemes basats en el coneixement i l'usuari presenta, doncs, nous reptes. Tot i que el llenguate natural es especialment apropiat per comunicar-se amb aquests sistemes, són pocs els que incorporen interfícies en llenguatge natural. Els motius principals són els problemes d'eficiència que presenta el processament del llenguatge natural i l'elevat cost de desenvolupar les bases de coneixement (conceptual i lingüístic) necessàries per a cada aplicació. L'objectiu d'aquesta tesi és millorar la comunicació en llenguatge natural amb els sistemes basats en el coneixement. Aquesta recerca s'ha centrat en el disseny d'una representació reutilitzable dels diferents tipus de coneixement involucrats en aquesta comunicació, que permetir de generar de forma automàtica la interfície més adequada per a cada aplicació. S'ha desenvolupat un sistema, GISE (Generador de Interfaces a Sistemas Expertos), que genera interfícies en llenguatge natural per diferents tipus d'aplicacions. Aquest sistema adapta automàticament les bases de coneixement lingüístic generals als requeriments d'una aplicació concreta, obtenint la gramàtica més apropiada. El disseny del sistema està basat en una representació reutilitzable i modular dels diferents tipus de coneixement necessaris en la comunicació en llenguatge natural. Aquesta informació consisteix en els conceptes de l'aplicació, les tasques de comunicació, el coneixement lingüístic i les relacions generals entre el coneixement conceptual i la seva realització lingüística. Tres bases de coneixement s'han dissenyat per representar aquesta informació: la ontologia conceptual, la ontologia lingüística i un conjunt de relges de producció. El coneixement conceptual s'ha representat en la ontologia conceptual. Aquest coneixement inclou aspectes sobre el domini i la funcionalitat. Tota la informació necessària per modelar l'aplicació i tots els possibles actes de comunicació estan representats en la ontologia conceptual. La complexitat dels sistemes basats en el coneixement fa necessària una representació formal i explícita de la seva funcionalitat i domini.El coneixement lingüístic general necessari per expressar en llenguatge natural les possibles tasques del sistema es representen en la ontologia lingüística.La informació que permet relacionar el coneixement lingüístic general a una aplicació concreta per tal d'obtenir la gramàtica més adequada es representada mitjançant un conjunt de regles de producció.L'organització modular dels diferents tipus de coneixement que intervenen en la comunicació facilita l'adaptació del sistema a diferents tipus d'aplicacions i usuaris.Les gramàtiques generades pel sistema GISE utilitzen un llenguatge alhora ric i precís, adaptat a l'aplicació. La interfície del sistema incorpora un sistema de finestres que guia a l'usuari a introduir les opcions en llenguatge natural que el sistema reconeix.GISE s'ha aplicat a diferents sistemes: a SIREDOJ, un sistema expert en lleis i a un sistema que dóna informació sobre trens.Since the 1980's, knowledge based systems (KBSs), programs that use knowledge to model situations and solve problems, have spread throughout industry, finance and science. Human communication with these systems deals with complex concepts and relationships that are not present in other software applications. Allthough the natural language (NL) is especially appropriate for expressing these concepts, there are not many KBSs incorporating NL interfaces. The main reasons for this are problems of efficiency in NLI performance, lack of adequacy to the communication needs of the applications and the high cost of developing and maintaining them.The aim of this thesis is to study how the communication process and engineering features can be improved in NL interaction with KBSs. This study has been focused on the efficient and reusable representation of the knowledge involved in NL communication with KBSs. GISE (Generador de Interfaces a Sistemas Expertos), a system supporting NL communication with KBSs has been developed. This system adapts the general linguistic resources to application requirements in order to automatically obtain application-restricted grammars. The main issue of the system design is a separate and reusable representation of all types of knowledge involved in communication with KBSs. This knowledge consists of the application knowledge appearing in the communication, the tasks of communication, the linguistic knowledge supporting their expression and the general relationships between conceptual knowledge and its linguistic realization. Three general bases were designed to represent all this knowledge : the Conceptual Ontology (CO), the Linguistic Ontology (LO) and a set of control rules.Conceptual knowledge is represented in the CO. This conceptual knowledge includes domain and functionality issues. All knowledge required to model the applications as well as the description of all possible communication acts is provided in the CO. The CO is the skeleton for anchoring the domain and the functionality of the applications. The complexity of KBS performance makes a formal and explicit representation of their domain and functionality necessary. The general linguistic knowledge needed to cover the expression in NL of the tasks the system performs is represented by means of the LO and a set containing all possible realizations of the application terms. The LO is domain and application independent. The control information to relate the general linguistic knowledge to conceptual application knowledge in order to generate the application-restricted grammars is represented by a set of production rules. The modular organization of the relevant knowledge into separate data structures provides great flexibility for adapting the system to different types of applications and users.The grammars generated by GISE use expressive and precise language tuned to the application and adapted to the evolution of the communicative process. A menu-system to guide the user in introducing the NL is integrated into the GISE interface. GISE has been applied to a couple of applications: SIREDOJ, an ES in law and a railway communication system

Creation and extension of ontologies for describing communications in the context of organizations

Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfillment of the requirements for the degree of Master in Computer ScienceThe use of ontologies is nowadays a sufficiently mature and solid field of work to be considered an efficient alternative in knowledge representation. With the crescent growth of the Semantic Web, it is expectable that this alternative tends to emerge even more in the near future. In the context of a collaboration established between FCT-UNL and the R&D department of a national software company, a new solution entitled ECC – Enterprise Communications Center was developed. This application provides a solution to manage the communications that enter, leave or are made within an organization, and includes intelligent classification of communications and conceptual search techniques in a communications repository. As specificity may be the key to obtain acceptable results with these processes, the use of ontologies becomes crucial to represent the existing knowledge about the specific domain of an organization. This work allowed us to guarantee a core set of ontologies that have the power of expressing the general context of the communications made in an organization, and of a methodology based upon a series of concrete steps that provides an effective capability of extending the ontologies to any business domain. By applying these steps, the minimization of the conceptualization and setup effort in new organizations and business domains is guaranteed. The adequacy of the core set of ontologies chosen and of the methodology specified is demonstrated in this thesis by its effective application to a real case-study, which allowed us to work with the different types of sources considered in the methodology and the activities that support its construction and evolution

PowerAqua: Open Question Answering on the Semantic Web

With the rapid growth of semantic information in the Web, the processes of searching and querying these very large amounts of heterogeneous content have become increasingly challenging. This research tackles the problem of supporting users in querying and exploring information across multiple and heterogeneous Semantic Web (SW) sources. A review of literature on ontology-based Question Answering reveals the limitations of existing technology. Our approach is based on providing a natural language Question Answering interface for the SW, PowerAqua. The realization of PowerAqua represents a considerable advance with respect to other systems, which restrict their scope to an ontology-specific or homogeneous fraction of the publicly available SW content. To our knowledge, PowerAqua is the only system that is able to take advantage of the semantic data available on the Web to interpret and answer user queries posed in natural language. In particular, PowerAqua is uniquely able to answer queries by combining and aggregating information, which can be distributed across heterogeneous semantic resources. Here, we provide a complete overview of our work on PowerAqua, including: the research challenges it addresses; its architecture; the techniques we have realised to map queries to semantic data, to integrate partial answers drawn from different semantic resources and to rank alternative answers; and the evaluation studies we have performed, to assess the performance of PowerAqua. We believe our experiences can be extrapolated to a variety of end-user applications that wish to open up to large scale and heterogeneous structured datasets, to be able to exploit effectively what possibly is the greatest wealth of data in the history of Artificial Intelligence