On the upcoming colloquium, Ivan Ermilov and Konrad Höffner, members of AKSW, will present two papers from the natural language processing (NLP) and Question Answering (QA) research areas.
ClausIE: Clause-Based Open Information Extraction
Authors. Del Corro, Luciano, and Rainer Gemulla.
Abstract. We propose ClausIE, a novel, clause-based approach to open information extraction, which extracts relations and their arguments from natural language text. ClausIE fundamentally differs from previous approaches in that it separates the detection of “useful” pieces of information expressed in a sentence from their representation in terms of extractions. In more detail, ClausIE exploits linguistic knowledge about the grammar of the English language to first detect clauses in an input sentence and to subsequently identify the type of each clause according to the grammatical function of its constituents. Based on this information, ClausIE is able to generate high-precision extractions; the representation of these extractions can be flexibly customized to the underlying application. ClausIE is based on dependency parsing and a small set of domain-independent lexica, operates sentence by sentence without any post-processing, and requires no training data (whether labeled or unlabeled). Our experimental study on various real-world datasets suggests that ClausIE obtains higher recall and higher precision than existing approaches, both on high-quality text as well as on noisy text as found in the web.
A Joint Model for Question Answering over Multiple Knowledge Bases
Authors. Zhang, Yuanzhe, et al.
Abstract. As the amount of knowledge bases (KBs) grows rapidly, the problem of question answering (QA) over multiple KBs has drawn more attention. The most significant distinction between multiple KB-QA and single KB-QA is that the former must consider the alignments between KBs. The pipeline strategy first constructs the alignments independently, and then uses the obtained alignments to construct queries. However, alignment construction is not a trivial task, and the introduced noises would be passed on to query construction. By contrast, we notice that alignment construction and query construction are interactive steps, and jointly considering them would be beneficial. To this end, we present a novel joint model based on integer linear programming (ILP), uniting these two procedures into a uniform framework. The experimental results demonstrate that the proposed approach outperforms stateof-the-art systems, and is able to improve the performance of both alignment construction and query construction.
Each talk will last for 20 minutes. The audience will have 10 minutes to ask questions. There will be cookies and coffee break after the talks for discussion as well.
In the incoming AKSW Colloquium, scheduled for the 14th of December at 3 PM, 
On the 7th of December at 3 PM, 
On November 30 at 3 PM, 
(right) will present SCARO. Afterwards, 
René Speck
GraphLab is a graph-based distributed computation framework. It was developed from 2009 at Carnegie Mellon University. At that time it was competing with Hadoop on Graph processing. The typical example algorithm demonstrated with it is the PageRank calculation. It still appears today in the Spark GraphX documentation as a filler for the computation step. We will look at the architecture, sample code and what happened to GraphLab today.
On November 2nd at 3 PM, 