ترغب بنشر مسار تعليمي؟ اضغط هنا

Top-k Query Answering in Datalog+/- Ontologies under Subjective Reports (Technical Report)

146   0   0.0 ( 0 )
 نشر من قبل Gerardo Simari
 تاريخ النشر 2013
  مجال البحث الهندسة المعلوماتية
والبحث باللغة English




اسأل ChatGPT حول البحث

The use of preferences in query answering, both in traditional databases and in ontology-based data access, has recently received much attention, due to its many real-world applications. In this paper, we tackle the problem of top-k query answering in Datalog+/- ontologies subject to the querying users preferences and a collection of (subjective) reports of other users. Here, each report consists of scores for a list of features, its authors preferences among the features, as well as other information. Theses pieces of information of every report are then combined, along with the querying users preferences and his/her trust into each report, to rank the query results. We present two alternative such rankings, along with algorithms for top-k (atomic) query answering under these rankings. We also show that, under suitable assumptions, these algorithms run in polynomial time in the data complexity. We finally present more general reports, which are associated with sets of atoms rather than single atoms.



قيم البحث

اقرأ أيضاً

Answering logical queries over incomplete knowledge bases is challenging because: 1) it calls for implicit link prediction, and 2) brute force answering of existential first-order logic queries is exponential in the number of existential variables. R ecent work of query embeddings provides fast querying, but most approaches model set logic with closed regions, so lack negation. Query embeddings that do support negation use densities that suffer drawbacks: 1) only improvise logic, 2) use expensive distributions, and 3) poorly model answer uncertainty. In this paper, we propose Logic Embeddings, a new approach to embedding complex queries that uses Skolemisation to eliminate existential variables for efficient querying. It supports negation, but improves on density approaches: 1) integrates well-studied t-norm logic and directly evaluates satisfiability, 2) simplifies modeling with truth values, and 3) models uncertainty with truth bounds. Logic Embeddings are competitively fast and accurate in query answering over large, incomplete knowledge graphs, outperform on negation queries, and in particular, provide improved modeling of answer uncertainty as evidenced by a superior correlation between answer set size and embedding entropy.
We develop a query answering system, where at the core of the work there is an idea of query answering by rewriting. For this purpose we extend the DL DL-Lite with the ability to support n-ary relations, obtaining the DL DLR-Lite, which is still poly nomial in the size of the data. We devise a flexible way of mapping the conceptual level to the relational level, which provides the users an SQL-like query language over the conceptual schema. The rewriting technique adds value to conventional query answering techniques, allowing to formulate simpler queries, with the ability to infer additional information that was not stated explicitly in the user query. The formalization of the conceptual schema and the developed reasoning technique allow checking for consistency between the database and the conceptual schema, thus improving the trustiness of the information system.
We investigate the problem whether two ALC ontologies are indistinguishable (or inseparable) by means of queries in a given signature, which is fundamental for ontology engineering tasks such as ontology versioning, modularisation, update, and forget ting. We consider both knowledge base (KB) and TBox inseparability. For KBs, we give model-theoretic criteria in terms of (finite partial) homomorphisms and products and prove that this problem is undecidable for conjunctive queries (CQs), but 2ExpTime-complete for unions of CQs (UCQs). The same results hold if (U)CQs are replaced by rooted (U)CQs, where every variable is connected to an answer variable. We also show that inseparability by CQs is still undecidable if one KB is given in the lightweight DL EL and if no restrictions are imposed on the signature of the CQs. We also consider the problem whether two ALC TBoxes give the same answers to any query over any ABox in a given signature and show that, for CQs, this problem is undecidable, too. We then develop model-theoretic criteria for Horn-ALC TBoxes and show using tree automata that, in contrast, inseparability becomes decidable and 2ExpTime-complete, even ExpTime-complete when restricted to (unions of) rooted CQs.
Conversational Question Answering is a challenging task since it requires understanding of conversational history. In this project, we propose a new system RoBERTa + AT +KD, which involves rationale tagging multi-task, adversarial training, knowledge distillation and a linguistic post-process strategy. Our single model achieves 90.4(F1) on the CoQA test set without data augmentation, outperforming the current state-of-the-art single model by 2.6% F1.
In modern application areas for software systems --- like eHealth, the Internet-of-Things, and Edge Computing --- data is encoded in heterogeneous, tree-shaped data-formats, it must be processed in real-time, and it must be ephemeral, i.e., not persi st in the system. While it is preferable to use a query language to express complex data-handling logic, their typical execution engine, a database external from the main application, is unfit in scenarios of ephemeral data-handling. A better option is represented by integrated query frameworks, which benefit from existing development support tools (e.g., syntax and type checkers) and execute within the application memory. In this paper, we propose one such framework that, for the first time, targets tree-shaped, document-oriented queries. We formalise an instantiation of MQuery, a sound variant of the widely-used MongoDB query language, which we implemented in the Jolie language. Jolie programs are microservices, the building blocks of modern software systems. Moreover, since Jolie supports native tree data-structures and automatic management of heterogeneous data-encodings, we can provide a uniform way to use MQuery on any data-format supported by the language. We present a non-trivial use case from eHealth, use it to concretely evaluate our model, and to illustrate our formalism.

الأسئلة المقترحة

التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا