Commit a69c13e4 authored by Alexander Hinneburg's avatar Alexander Hinneburg
Browse files

Reihenfolge

parent 4536da3d
......@@ -11,7 +11,7 @@ die in die Forschung der Arbeitsgruppen (HiWi, Abschlussarbeiten, Forschungsproj
- **Nächster Termin: Donnerstag 23.1.2020 16.00-18.00 Uhr**
- **Raum: 3.31**
- **Deadline für Vortragsanmeldung: Mittwoch 8.1.2020**
- ~~**Deadline für Vortragsanmeldung: Mittwoch 8.1.2020**~~
<details>
<summary>
......@@ -39,31 +39,31 @@ die in die Forschung der Arbeitsgruppen (HiWi, Abschlussarbeiten, Forschungsproj
- **Eröffnung**
1. **Maik Fröbe**, Big Data Analytics
**Hidden Oversampling in Learning-to-Rank**
The machine learning approaches to solve the problem of ranking in search engines rely on vast amounts of training data. Those training datasets contain duplicated documents that are unexpected in subsequent machine learning algorithms. We investigate the impact of that "hidden oversampling" to the produced rankings of the search engine.
2. **Alexander Bondarenko**, Big Data Analytics
1. **Alexander Bondarenko**, Big Data Analytics
**Comparative Web Search Questions**
Users ask comparative questions, i.e., questions asking to compare different items, not only on community question answering platforms like Yahoo! Answers, Quora, or StackExchange, but also submit as queries to search engines. Responses to such questions might be quite different from the simple ''ten blue links'' and could, for example, aggregate pros and cons of the different options as direct answers. We analyze such questions and propose methods to answering them.
3. **Ekaterina Shirshakova**, Big Data Analytics
2. **Ekaterina Shirshakova**, Big Data Analytics
**Same Side Stance Classification**
In recent years, the popularity of social media and online discussions has lead to a rise of pro and con argumentation for various topics. Still, since not all contributions in such online discussions clearly indicate a stance or polarity of the contribution, automatically identifying some post's stance (in social media platforms, etc.) could help readers quickly get an overview of a discussion similar to debating portals with pro/con arguments.
4. **Mario Wenzel**, Datenbanken und Informationssysteme
3. **Mario Wenzel**, Datenbanken und Informationssysteme
**Microlog - Datalog for microcontrollers**
Datalog or variants thereof are prevalent in an uncountable number of software systems. An area that seems ideal for rule-based programming, microcontrollers, is underserved by logic programming approaches. Microlog aims to close that gap by providing a standalone framework for deductive reasoning in interactive systems.
5. **Silvio Weging**, Bioinformatik
4. **Silvio Weging**, Bioinformatik
**kASA: Taxonomic Analysis of Metagenomic Data on a Notebook**
The taxonomic analysis of metagenomic sequencing data has become important in many areas of life sciences. However, currently available software tools for that purpose either consume large amounts of RAM or yield an insufficient quality of the results. To identify and profile metagenomic sequences with high computational efficiency and a small user-definable memory footprint, we developed a k-mer based software named "kASA".
5. **Maik Fröbe**, Big Data Analytics
**Hidden Oversampling in Learning-to-Rank**
The machine learning approaches to solve the problem of ranking in search engines rely on vast amounts of training data. Those training datasets contain duplicated documents that are unexpected in subsequent machine learning algorithms. We investigate the impact of that "hidden oversampling" to the produced rankings of the search engine.
6. **Annett Erkes**, Bioinformatik
**Bioinformatic analysis of TAL effectors in the Xanthomonas oryzae - rice interaction**
Diseases caused by plant-pathogenic Xanthomonas bacteria are a serious threat for many important crop plants including rice. Efficiently protecting plants from these pathogens requires a deeper understanding of infection strategies. Such infection strategies depend on a special class of effector
proteins, termed transcription activator-like effectors (TALEs). Our approach PrediTALE predicts plant target genes of TALEs.
7. **Vaibhav Kasturia**, Big Data Analytics
**Entity-Based Query Interpretation**
We address the problem of entity-based query interpretation: given a keyword query, what accepted meanings can the query have with respect to potentially ambiguous contained entities. To tackle this problem, we separate three entity recognition problems: explicit entity recognition, implicit entity recognition and related entity recognition. Based on these problems, we define entity-based query interpretation and introduce a new corpus containing 2800 queries with explicit and implicit entities as well as with query interpretations. Using query segmentation, the possible meanings of a query are output based on the entities contained in the query.
8. **Maximilian Konzack**, Datenbanken und Informationssysteme / iDiv
7. **Maximilian Konzack**, Datenbanken und Informationssysteme / iDiv
**Information extraction from ecological publications**
Biodiversity datasets are increasingly deposited either as supplementary material in an article or in online repositories. As more and more scientific papers are digitally published, we face new challenges to find, access, integrate and reuse publications and their associated datasets. In this talk, I will talk about methodologies in which I employ text classification and geoparsing to tackle some of these problems.
8. **Vaibhav Kasturia**, Big Data Analytics
**Entity-Based Query Interpretation**
We address the problem of entity-based query interpretation: given a keyword query, what accepted meanings can the query have with respect to potentially ambiguous contained entities. To tackle this problem, we separate three entity recognition problems: explicit entity recognition, implicit entity recognition and related entity recognition. Based on these problems, we define entity-based query interpretation and introduce a new corpus containing 2800 queries with explicit and implicit entities as well as with query interpretations. Using query segmentation, the possible meanings of a query are output based on the entities contained in the query.
9. **Marcus Pöckelmann**, Informatik in den Geisteswissenschaften
**Collation and analysis of Hebrew text witnesses**
The Hebrew treatise Keter Shem Ṭov (“Crown of the Good Name”) composed in the 13th century is one of the most important introductory texts into the Kabbalah, testified by about 100 differing manuscripts. In our current project, an interdisciplinary team prepares a scholarly edition of this work with the aid of our tool LERA that has to be adopted for this task. The focus here is on the enormous number of text witnesses, which poses a challenge for both the underlying algorithms and the user interface of LERA.
......@@ -73,3 +73,4 @@ proteins, termed transcription activator-like effectors (TALEs). Our approach Pr
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment