Search Results for author: Gerhard Weikum

Found 83 papers, 20 papers with code

CHARM: Inferring Personal Attributes from Conversations

no code implementations EMNLP 2020 Anna Tigunova, Andrew Yates, Paramita Mirza, Gerhard Weikum

Personal knowledge about users{'} professions, hobbies, favorite food, and travel preferences, among others, is a valuable asset for individualized AI, such as recommenders or chatbots.

Keyword Extraction Zero-Shot Learning

Language Models As or For Knowledge Bases

no code implementations10 Oct 2021 Simon Razniewski, Andrew Yates, Nora Kassner, Gerhard Weikum

Pre-trained language models (LMs) have recently gained attention for their potential as an alternative to (or proxy for) explicit knowledge bases (KBs).

Complex Temporal Question Answering on Knowledge Graphs

1 code implementation18 Sep 2021 Zhen Jia, Soumajit Pramanik, Rishiraj Saha Roy, Gerhard Weikum

This work presents EXAQT, the first end-to-end system for answering complex temporal questions that have multiple entities and predicates, and associated temporal conditions.

Entity Embeddings Knowledge Graphs +1

Personalized Entity Search by Sparse and Scrutable User Profiles

no code implementations10 Sep 2021 Ghazaleh Haratinezhad Torbati, Andrew Yates, Gerhard Weikum

Prior work on personalizing web search results has focused on considering query-and-click logs to capture users individual interests.

Re-Ranking

You Get What You Chat: Using Conversations to Personalize Search-based Recommendations

no code implementations10 Sep 2021 Ghazaleh Haratinezhad Torbati, Andrew Yates, Gerhard Weikum

The paper develops an expressive model and effective methods for personalizing search-based entity recommendations.

Re-Ranking

Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty Learning

no code implementations9 Sep 2021 Preethi Lahoti, Krishna P. Gummadi, Gerhard Weikum

Reliably predicting potential failure risks of machine learning (ML) systems when deployed with production data is a crucial aspect of trustworthy AI.

UNIQORN: Unified Question Answering over RDF Knowledge Graphs and Natural Language Text

no code implementations19 Aug 2021 Soumajit Pramanik, Jesujoba Alabi, Rishiraj Saha Roy, Gerhard Weikum

Question answering over knowledge graphs and other RDF data has been greatly advanced, with a number of good systems providing crisp answers for natural language questions or telegraphic queries.

Knowledge Graphs Question Answering

Beyond NED: Fast and Effective Search Space Reduction for Complex Question Answering over Knowledge Bases

no code implementations19 Aug 2021 Philipp Christmann, Rishiraj Saha Roy, Gerhard Weikum

Answering complex questions over knowledge bases (KB-QA) faces huge input data with billions of facts, involving millions of entities and thousands of predicates.

Entity Disambiguation Knowledge Graphs +1

AligNarr: Aligning Narratives on Movies

1 code implementation ACL 2021 Paramita Mirza, Mostafa Abouhamra, Gerhard Weikum

High-quality alignment between movie scripts and plot summaries is an asset for learning to summarize stories and to generate dialogues.

Global Optimization

Reinforcement Learning from Reformulations in Conversational Question Answering over Knowledge Graphs

1 code implementation11 May 2021 Magdalena Kaiser, Rishiraj Saha Roy, Gerhard Weikum

We present a reinforcement learning model, termed CONQUER, that can learn from a conversational stream of questions and reformulations.

Knowledge Graphs Question Answering

SANDI: Story-and-Images Alignment

no code implementations EACL 2021 Sreyasi Nag Chowdhury, Simon Razniewski, Gerhard Weikum

The Internet contains a multitude of social media posts and other of stories where text is interspersed with images.

ELIXIR: Learning from User Feedback on Explanations to Improve Recommender Models

1 code implementation15 Feb 2021 Azin Ghazimatin, Soumajit Pramanik, Rishiraj Saha Roy, Gerhard Weikum

System-provided explanations for recommendations are an important component towards transparent and trustworthy AI.

Cross-Domain Learning for Classifying Propaganda in Online Contents

2 code implementations13 Nov 2020 Liqiang Wang, Xiaoyu Shen, Gerard de Melo, Gerhard Weikum

Prior work has focused on supervised learning with training data from the same domain.

Advanced Semantics for Commonsense Knowledge Extraction

1 code implementation2 Nov 2020 Tuan-Phong Nguyen, Simon Razniewski, Gerhard Weikum

Commonsense knowledge (CSK) about concepts and their properties is useful for AI applications such as robust chatbots.

Commonsense Knowledge Base Construction

Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases

no code implementations24 Sep 2020 Gerhard Weikum, Luna Dong, Simon Razniewski, Fabian Suchanek

Equipping machines with comprehensive knowledge of the world's entities and their relationships has been a long-standing goal of AI.

Knowledge Graphs Question Answering

CounQER: A System for Discovering and Linking Count Information in Knowledge Bases

1 code implementation7 May 2020 Shrestha Ghosh, Simon Razniewski, Gerhard Weikum

Predicate constraints of general-purpose knowledge bases (KBs) like Wikidata, DBpedia and Freebase are often limited to subproperty, domain and range constraints.

Question Answering

RedDust: a Large Reusable Dataset of Reddit User Traits

no code implementations LREC 2020 Anna Tigunova, Paramita Mirza, Andrew Yates, Gerhard Weikum

To the best of our knowledge, RedDust is the first annotated language resource about Reddit users at large scale.

Conversational Question Answering over Passages by Leveraging Word Proximity Networks

1 code implementation27 Apr 2020 Magdalena Kaiser, Rishiraj Saha Roy, Gerhard Weikum

In this work, we demonstrate CROWN (Conversational passage ranking by Reasoning Over Word Networks): an unsupervised yet effective system for conversational QA with passage responses, that supports several modes of context propagation over multiple turns.

Information Retrieval Question Answering

Uncovering Hidden Semantics of Set Information in Knowledge Bases

1 code implementation6 Mar 2020 Shrestha Ghosh, Simon Razniewski, Gerhard Weikum

This paper focuses on set-valued predicates, i. e., the relationship between an entity and a set of entities.

Question Answering

Negative Statements Considered Useful

no code implementations13 Jan 2020 Hiba Arnaout, Simon Razniewski, Gerhard Weikum, Jeff Z. Pan

Negative statements are useful to overcome limitations of question answering systems that are mainly geared for positive questions; they can also contribute to informative summaries of entities.

Question Answering

Joint Reasoning for Multi-Faceted Commonsense Knowledge

1 code implementation13 Jan 2020 Yohan Chalier, Simon Razniewski, Gerhard Weikum

Each concept is treated in isolation from other concepts, and the only quantitative measure (or ranking) of properties is a confidence score that the statement is valid.

PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender Systems

1 code implementation19 Nov 2019 Azin Ghazimatin, Oana Balalau, Rishiraj Saha Roy, Gerhard Weikum

Interpretable explanations for recommender systems and other machine learning models are crucial to gain user trust.

Recommendation Systems

CROWN: Conversational Passage Ranking by Reasoning over Word Networks

1 code implementation7 Nov 2019 Magdalena Kaiser, Rishiraj Saha Roy, Gerhard Weikum

Information needs around a topic cannot be satisfied in a single turn; users typically ask follow-up questions referring to the same theme and a system must be capable of understanding the conversational context of a request to retrieve correct answers.

Coverage of Information Extraction from Sentences and Paragraphs

no code implementations IJCNLP 2019 Simon Razniewski, Nitisha Jain, Paramita Mirza, Gerhard Weikum

Scalar implicatures are language features that imply the negation of stronger statements, e. g., {``}She was married twice{''} typically implicates that she was not married thrice.

Know2Look: Commonsense Knowledge for Visual Search

no code implementations WS 2016 Sreyasi Nag Chowdhury, Niket Tandon, Gerhard Weikum

With the rise in popularity of social media, images accompanied by contextual text form a huge section of the web.

Story-oriented Image Selection and Placement

no code implementations2 Sep 2019 Sreyasi Nag Chowdhury, Simon Razniewski, Gerhard Weikum

Multimodal contents have become commonplace on the Internet today, manifested as news articles, social media posts, and personal or business blog posts.

Combinatorial Optimization Object Recognition

TEQUILA: Temporal Question Answering over Knowledge Bases

no code implementations9 Aug 2019 Zhen Jia, Abdalghani Abujabal, Rishiraj Saha Roy, Jannik Stroetgen, Gerhard Weikum

An important case, addressed here, is that of temporal questions, where cues for temporal relations need to be discovered and handled.

Question Answering

FAIRY: A Framework for Understanding Relationships between Users' Actions and their Social Feeds

1 code implementation8 Aug 2019 Azin Ghazimatin, Rishiraj Saha Roy, Gerhard Weikum

We model the user's local neighborhood on the platform as an interaction graph, a form of heterogeneous information network constructed solely from information that is easily accessible to the concerned user.

Learning-To-Rank

Operationalizing Individual Fairness with Pairwise Fair Representations

no code implementations2 Jul 2019 Preethi Lahoti, Krishna P. Gummadi, Gerhard Weikum

We revisit the notion of individual fairness proposed by Dwork et al. A central challenge in operationalizing their approach is the difficulty in eliciting a human specification of a similarity metric.

Fairness

Neural Relation Extraction for Knowledge Base Enrichment

no code implementations ACL 2019 Bayu Distiawan Trisedya, Gerhard Weikum, Jianzhong Qi, Rui Zhang

This way, NED errors may cause extraction errors that affect the overall precision and recall. To address this problem, we propose an end-to-end relation extraction model for KB enrichment based on a neural encoder-decoder model.

Entity Disambiguation Entity Embeddings +1

Commonsense Properties from Query Logs and Question Answering Forums

2 code implementations27 May 2019 Julien Romero, Simon Razniewski, Koninika Pal, Jeff Z. Pan, Archit Sakhadeo, Gerhard Weikum

Commonsense knowledge about object properties, human behavior and general concepts is crucial for robust AI applications.

Question Answering

Listening between the Lines: Learning Personal Attributes from Conversations

1 code implementation24 Apr 2019 Anna Tigunova, Andrew Yates, Paramita Mirza, Gerhard Weikum

Open-domain dialogue agents must be able to converse about many topics while incorporating knowledge about the user into the conversation.

TiFi: Taxonomy Induction for Fictional Domains [Extended version]

no code implementations29 Jan 2019 Cuong Xuan Chu, Simon Razniewski, Gerhard Weikum

Taxonomies are important building blocks of structured knowledge bases, and their construction from text sources and Wikipedia has received much attention.

Facts That Matter

1 code implementation EMNLP 2018 Marco Ponza, Luciano del Corro, Gerhard Weikum

This work introduces fact salience: The task of generating a machine-readable representation of the most prominent information in a text document as a set of facts.

Entity Linking Open Information Extraction +3

ComQA: A Community-sourced Dataset for Complex Factoid Question Answering with Paraphrase Clusters

no code implementations NAACL 2019 Abdalghani Abujabal, Rishiraj Saha Roy, Mohamed Yahya, Gerhard Weikum

To bridge the gap between the capabilities of the state-of-the-art in factoid question answering (QA) and what users ask, we need large datasets of real user questions that capture the various question phenomena users are interested in, and the diverse ways in which these questions are formulated.

Question Answering

Enriching Knowledge Bases with Counting Quantifiers

1 code implementation10 Jul 2018 Paramita Mirza, Simon Razniewski, Fariz Darari, Gerhard Weikum

In a large-scale experiment, we demonstrate the potential for knowledge base enrichment by applying CINEX to 2, 474 frequent relations in Wikidata.

iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making

no code implementations4 Jun 2018 Preethi Lahoti, Krishna P. Gummadi, Gerhard Weikum

We demonstrate the versatility of our method by applying it to classification and learning-to-rank tasks on a variety of real-world datasets.

Decision Making Fairness +1

Equity of Attention: Amortizing Individual Fairness in Rankings

no code implementations4 May 2018 Asia J. Biega, Krishna P. Gummadi, Gerhard Weikum

We formulate the challenge of achieving amortized individual fairness subject to constraints on ranking quality as an online optimization problem and show that it can be solved as an integer linear program.

Fairness Recommendation Systems

KnowNER: Incremental Multilingual Knowledge in Named Entity Recognition

no code implementations11 Sep 2017 Dominic Seyler, Tatiana Dembelova, Luciano del Corro, Johannes Hoffart, Gerhard Weikum

KnowNER is a multilingual Named Entity Recognition (NER) system that leverages different degrees of external knowledge.

Named Entity Recognition NER

Credible Review Detection with Limited Information using Consistency Analysis

no code implementations7 May 2017 Subhabrata Mukherjee, Sourav Dutta, Gerhard Weikum

Online reviews provide viewpoints on the strengths and shortcomings of products/services, influencing potential customers' purchasing decisions.

Topic Models

People on Media: Jointly Identifying Credible News and Trustworthy Citizen Journalists in Online Communities

no code implementations7 May 2017 Subhabrata Mukherjee, Gerhard Weikum

This paper presents a model to systematically analyze the different interactions in a news community between users, news, and sources.

Fairness

Exploring Latent Semantic Factors to Find Useful Product Reviews

no code implementations6 May 2017 Subhabrata Mukherjee, Kashyap Popat, Gerhard Weikum

In this work, we attempt to automatically identify review quality in terms of its helpfulness to the end consumers.

Item Recommendation with Evolving User Preferences and Experience

no code implementations6 May 2017 Subhabrata Mukherjee, Hemank Lamba, Gerhard Weikum

As only item ratings and review texts are observables, we capture the user's experience and interests in a latent model learned from her reviews, vocabulary and writing style.

Collaborative Filtering Recommendation Systems

Cardinal Virtues: Extracting Relation Cardinalities from Text

no code implementations ACL 2017 Paramita Mirza, Simon Razniewski, Fariz Darari, Gerhard Weikum

Information extraction (IE) from text has largely focused on relations between individual entities, such as who has won which award.

KOGNAC: Efficient Encoding of Large Knowledge Graphs

1 code implementation16 Apr 2016 Jacopo Urbani, Sourav Dutta, Sairam Gurajada, Gerhard Weikum

We propose KOGNAC, a dictionary-encoding algorithm designed to improve SPARQL querying with a judicious combination of statistical and semantic techniques.

Knowledge Graphs

Cross-Document Co-Reference Resolution using Sample-Based Clustering with Knowledge Enrichment

no code implementations TACL 2015 Sourav Dutta, Gerhard Weikum

Second, we reduce the computational cost by a new algorithm that embeds sample-based bisection, using spectral clustering or graph partitioning, in a hierarchical clustering process.

Coreference Resolution graph partitioning +1

Robust Disambiguation of Named Entities in Text

no code implementations1 Jul 2011 Johannes Hoffart, Mohamed Amir Yosef, Ilaria Bordino, Hagen Fürstenau, Manfred Pinkal, Marc Spaniol, Bilyana Taneva, Stefan Thater, Gerhard Weikum

Disambiguating named entities in naturallanguage text maps mentions of ambiguous names onto canonical entities like people or places, registered in a knowledge base such as DBpedia or YAGO.

Entity Disambiguation Entity Linking

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