arrow_back Back to Science

Redesigning Document Viewer for Legal Documents

Adam RoegiestWinter Wei • March 11, 2018 • CHIIR 2018

In Mergers and Acquisition due diligence, lawyers are tasked with analyzing a collection of contracts and determine the level of risk that comes from a merger or acquisition. This process has historically been manual and resulted in only a small fraction of the collection being examined. This paper reports on the user-focused redesign of our document viewer that is used by clients to review documents and train machine learning algorithms to find pertinent information from these contracts.

We present an overview of the due diligence task and the user stories, generated through analysis of support tickets, user interviews, and usability testing sessions, that we used to redesign our document viewer to accommodate the variety of workflows that our clients employ. Additionally, we detail the important design decisions made and discuss the implications of our redesign beyond our particular use case.

Read the Paper

Read more papers

Science

Spectator: An Open Source Document Viewer

Many information retrieval tasks require viewing documents in some manner, whether this is to view information in context or to provide annotations for some downstream task (e.g., evaluation or system training). Building a high-quality document viewer often exceeds the resources of many researchers and so, in this paper, we describe the design and architecture of our new open-source document viewer, Spectator. In particular, we provide a look into the algorithmic details of how Spectator accomplishes tasks like mapping annotations back to the canonical document.

Science

On Tradeoffs Between Document Signature Methods for a Legal Due Diligence Corpus

While document signatures are a well established tool in IR, they have primarily been investigated in the context of web documents. Legal due diligence documents, by their nature, have more similar structure and language than we may expect out of standard web collections. Moreover, many due diligence systems strive to facilitate real-time interactions and so time from document ingestion to availability should be minimal. Such constraints further limit the possible solution space when identifying near duplicate documents.