21 February 2020, 10:00-11:00

ENS, S16

**Provenance Analysis for First-order Model Checking**

Is a given finite structure a model of a given first-order sentence? The provenance analysis of this question determines how its answer depends on the atomic facts that determine the structure. Provenance questions like this one have emerged in databases, scientific workflows, networks, formal verification, and other areas. In joint work with Erich Grädel (RWTH Aachen University) we extend the semiring provenance framework, developed in databases, to the first-order model checking problem. This provides a non-standard semantics for first-order logic that refines logical truth to values in commutative semirings: a semiring of provenance polynomials, the Viterbi semiring of confidence scores, access control semirings, etc. The semantics can be used to synthesize models based on criteria like maximum confidence or public access. Our uniform treatment of logical negation can be used to explain missing answers for queries, and failures of integrity constraints, as well to compute corresponding repairs that fix these issues. The work on repairs is also joint with Abdu Alawini, Jane Xu, and Waley Zhang (Penn).

]]>28 February 2020, 10:30-11:30

ENS, S16

**The Complexity of Answering Unions of Conjunctive Queries**

We discuss the complexity of enumerating (listing) the answers to a query over a relational database. In particular, we consider three variants: arbitrary order, uniformly random order, and random access. We focus on the class of join queries: Conjunctive Queries (CQs) and Unions of Conjunctive Queries (UCQs), and on the ability to list the answers with linear preprocessing and logarithmic time per answer. A known dichotomy classifies CQs into those that admit such enumeration and those that do not. I will talk about my research towards extending this dichotomy to UCQs. This generalization turns out to be quite challenging. For example, a union of tractable CQs may be intractable w.r.t. random access; on the other hand, a union of intractable CQs may be tractable w.r.t. enumeration.

Bio:

Nofar Carmeli is a Ph.D. student in the Data and Knowledge group at Technion, Israel Institute of Technology, advised by Prof. Benny Kimelfeld. Her research focuses on query optimization with guarantees using enumeration techniques. Nofar completed her BSc in 2015 in the Lapidim excellence program of the Computer Science Department of Technion.

Associate Professor | School of Computing Science

Simon Fraser University 8888 University Dr., Burnaby, B.C. V5A 1S6

13 February 2020, 10:30-11:30

ENS, S16

**Logic of Information Flows: Expressing Reachability and Cardinality Properties**

A challenge in descriptive complexity is to identify logics with low complexity that simultaneously express fundamental reachability and counting properties on unordered structures. We define a family of logics that allow fine control of the complexity of order-independent computations. The approach is based on adding the ability to reason about information propagations in first-order logic with fixed points, FO(FP). Two parameters are used to control expressiveness and complexity: the set of logical connectives and the expressiveness of atomic units. We restrict both and obtain a modal temporal (Dynamic) logic over monadic unions of conjunctive queries. A crucial component is a dynamic version of Hilbert’s Epsilon operator. We identify a fragment with polytime data complexity and show that it can express both reachability and counting properties on unordered structures. Finally, we formalize Epsilon-invariance property for this logic and conjecture its decidability.

]]>7 February 2020, 10:30-11:30

ENS, S16

**An Experimental Study of the Treewidth of Real-World Data**

Treewidth is a parameter that measures how tree-like a data instance is, and whether it can reasonably be decomposed into a data structure resembling a tree.

Many computation tasks are known to be tractable on data having small treewidth, but computing the treewidth of a given instance is intractable. This talk presents the first large-scale experimental study of treewidth and tree decompositions of real-world data, with a focus on graph data. We aim to find out which data, if any, can benefit of the wealth of algorithms for data of small treewidth. For each dataset, we obtain upper and lower bound estimations of their treewidth, and study the properties of their tree decompositions. We show in particular that, even when treewidth is high, using partial tree decompositions can result in data structures that can assist algorithms.

29 November 2019, 10:30-11:30

ENS, S16

**A Brief History of Knowledge Graph’s Main Ideas**

Knowledge Graphs can be considered to be fulfilling an early vision in Computer Science of creating intelligent systems that integrate knowledge and data at large scale. The term “Knowledge Graph” has rapidly gained popularity in academia and industry since Google popularized it in 2012. It is paramount to note that, regardless of the discussions on, and definitions of the “Knowledge Graph” term, it stems from scientific advancements in diverse research areas such as Semantic Web, Databases, Knowledge Representation and Reasoning, NLP, Machine Learning, among others.

The integration of ideas and techniques from such disparate disciplines give the richness to the notion of Knowledge Graph, but at the same time presents a challenge to practitioners and researchers to know how current advances develop from, and are rooted in, early techniques.

In this talk, Juan will provide a historical context on the roots of Knowledge Graphs grounded in the advancements of the computer science disciplines of Knowledge, Data and the combination thereof, starting from the 1950s.

For more details, please read the paper: http://knowledgegraph.today/paper.html

Bio: Juan F. Sequeda is the Principal Scientist at data.world. He joined through the acquisition of Capsenta, a company he founded as a spin-off from his research. He holds a PhD in Computer Science from The University of Texas at Austin.

Juan is the recipient of the NSF Graduate Research Fellowship, received 2nd Place in the 2013 Semantic Web Challenge for his work on ConstituteProject.org, Best Student Research Paper at the 2014 International Semantic Web Conference, the 2015 Best Transfer and Innovation Project awarded by the Institute for Applied Informatics and nominated for best papers multiple times. Juan is on the Editorial Board of the Journal of Web Semantics, member of multiple program committees (ISWC, ESWC, WWW, AAAI, IJCAI). He was the General Chair of AMW2018, PC chair of ISWC 2017 In-Use track, co-creator of COLD workshop (7 years co-located at ISWC). He has served as a bridge between academia and industry as the current chair of the Property Graph Schema Working Group, member of the Graph Query Languages task force of the Linked Data Benchmark Council (LDBC) and past invited expert member and standards editor at the World Wide Web Consortium (W3C).

Wearing his scientific hat, Juan’s goal is to reliably create knowledge from inscrutable data. His research interests are on the intersection of Logic and Data for (ontology-based) data integration and semantic/graph data management, and what now is called Knowledge Graphs.

Wearing his business hat, Juan is a product manager, does business development and strategy, technical sales and works with customers to understand their problems to translated back to R&D.

]]>ENS, S16

**Order-invariant first-order logic over hollow trees. **

Order-invariant first-order logic is the extension of first-order logic in which the usage of an additional ordering relation on the structure’s universe is allowed, provided that the evaluation of sentences is independent of the choice of a particular order. We show that the expressive power of order-invariant first-order logic collapses to first-order logic over hollow trees. A hollow tree is an unranked ordered tree where every non leaf node has at most four adjacent nodes: two siblings (left and right) and its first and last children. In particular there is no predicate for the linear order among siblings nor for the descendant relation. Moreover only the first and last nodes of a siblinghood are linked to their parent node, and the parent-child relation cannot be completely reconstructed in first-order.

ENS, S16

**Weighted Linear Bandits for Non-stationary environments.**

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* September 30, October 4, 7, 11, 14, 18 and 25, 2019.

* 10:30-12:00

* Room 3052 of the Sophie Germain Building, Université Paris-Diderot (1, place Auréie Nemours, 75013 Paris).

]]>ENS, S16

** Yann Ramusat : **Provenance-Based Routing in Probabilistic Graph Databases**.

Abstract: Optimizing routing queries over graphs is a rich research area with important applications, e.g., to road and transportation networks. Thanks to progress made during past decades, current-day systems are able to compute paths across cities in continent-sized areas, paths that are optimal in terms of distance or expected travel time. Nevertheless, the problem considered is very constrained, personal preferences cannot be handled effectively, and similar queries need to be computed separately. We explore a provenance-based framework as a way to extend the expressive power of routing queries, based on the idea of keeping track of meta-information about query results. This framework, useful to deal with such aspects as uncertainty or preferences, cannot always benefit of optimizations used for computing optimal routes, leading to impractical algorithms. The aim of our PhD is to improve on routing techniques based on provenance to apply them to real transportation networks.

** Quentin Manière : **Complexity of answering rooted counting queries over DL-Lite ontologies**.

12 July 2019, 10:30-11:30

ENS, S16

**Lean Kernels: A Bridge Between Justifications and Provenance**

A justification is a minimal set of constraints (or axioms) responsible for a consequence to follow from a knowledge base. Since the time required to find justifications depends on the size of the knowledge base, recent research has focused on trying to approximate the set of “relevant” axioms; that is, the union of all justifications. One such approximation is the lean kernel, which corresponds to the axioms that appear in at least one proof of the consequence. In this talk we will explore the notion of lean kernel, its properties, and its relation to the computation of provenance over knowledge bases.

Bio: Rafael Peñaloza is an Associate Professor at the University of Milano-Bicocca, Italy. He received his PhD from TU Dresden, Germany, where he remained as a post-doctoral researcher before moving briefly to the Free University of Bozen-Bolzano, Italy. His main research interests are on non-standard knowledge representation formalisms–mainly fuzzy and probabilistic logics–and reasoning services such as explanations and repairs.

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