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With the rising applications implemented in different domains, it is inevitable to require databases to adopt corresponding appropriate data models to store and exchange data derived from various sources. To handle these data models in a…
Many users turn to document retrieval systems (e.g. search engines) to seek answers to controversial questions. Answering such user queries usually require identifying responses within web documents, and aggregating the responses based on…
We present a multimodal search tool that facilitates retrieval of chemical reactions, molecular structures, and associated text from scientific literature. Queries may combine molecular diagrams, textual descriptions, and reaction data,…
The large scale of scholarly publications poses a challenge for scholars in information seeking and sensemaking. Bibliometrics, information retrieval (IR), text mining and NLP techniques could help in these search and look-up activities,…
Multimodal search has become increasingly important in providing users with a natural and effective way to ex-press their search intentions. Images offer fine-grained details of the desired products, while text allows for easily…
Identifying drug-target interactions is essential for developing effective therapeutics. Binding affinity quantifies these interactions, and traditional approaches rely on computationally intensive 3D structural data. In contrast, language…
Conversational interfaces that allow for intuitive and comprehensive access to digitally stored information remain an ambitious goal. In this thesis, we lay foundations for designing conversational search systems by analyzing the…
Language modeling has seen impressive progress over the last years, mainly prompted by the invention of the Transformer architecture, sparking a revolution in many fields of machine learning, with breakthroughs in chemistry and biology. In…
The biomedical literature contains a vast collection of omics studies, yet most published data remain functionally inaccessible for computational reuse. When raw data are deposited in public repositories, essential information for…
Searching large digital repositories can be extremely frustrating, as common list-based formats encourage users to adopt a convenience-sampling approach that favours chance discovery and random search, over meaningful exploration. We have…
AI is transforming pharmaceutical search, where traditional systems struggle with multimodal content and manual curation. Finder is a scalable AI-powered framework that unifies retrieval across text, images, audio, and video using hybrid…
From more than half a century ago indexing scientific articles has been studied intensively to provide a more efficient data retrieval and to conserve researchers invaluable time. In the last two decades with the emergence of the World Wide…
A significant part of human activity today consists of searching for a piece of information online, utilizing knowledge repositories. This endeavor may be time-consuming if the individual searching for the information is unfamiliar with the…
From the earliest days of computing, there have been tools to help shape narrative. Spell-checking, word counts, and readability analysis, give today's novelists tools that Dickens, Austen, and Shakespeare could only have dreamt of.…
Exploratory search aims to guide users through a corpus rather than pinpointing exact information. We propose an exploratory search system based on hierarchical clusters and document summaries using sentence embeddings. With sentence…
This paper introduces Redescription Model Mining, a novel approach to identify interpretable patterns across two datasets that share only a subset of attributes and have no common instances. In particular, Redescription Model Mining aims to…
The search of information in large text repositories has been plagued by the so-called document-query vocabulary gap, i.e. the semantic discordance between the contents in the stored document entities on the one hand and the human query on…
In this paper we present a novel interactive multimodal learning system, which facilitates search and exploration in large networks of social multimedia users. It allows the analyst to identify and select users of interest, and to find…
Traditional Online Public Access Catalogues (OPACs) are becoming less effective due to the rapid growth of scholarly literature. Conventional search methods, such as keyword indexing and Boolean queries, often fail to support efficient…
Digital libraries in the scientific domain provide users access to a wide range of information to satisfy their diverse information needs. Here, ranking results play a crucial role in users' satisfaction. Exploiting bibliometric metadata,…