International Business Machines Corporation

Yahoo! Inc.

Jasmine Novak

Andrew Stephen Tomkins

Shanmugasundaram Ravikumar

Prabhakar Raghavan

Joseph Andrew Magnani

Micah Dubinko

Ramanathan V Guha

Dandapani Sivakumar

Ronald Fagin

Cameron A Marlow

Daniel Gruhl

Kevin Snow McCurley

John Anthony Tomlin

Phokion Kolaitis

David Paul Williamson

Ravi Kumar

Shanmugasundram Ravikumar

A method and apparatus are provided for detecting and explaining bursty stream events in targeted groups. In one example, the method includes receiving validated bursty events, finding explanatory data sources having relevant bursty events that are relevant to the validated bursty events, wherein the explanatory sources explain the presence of the validated bursty events, correlating the validated bursty events to the relevant bursty events of the explanatory data sources to obtain burst results, and sending the burst results to a burst database that is accessible to an end user.

Method and apparatus for detecting and explaining bursty stream events in targeted groups

Methods and systems are described for navigating a corpus of content items stored in one or more information repositories within a distributed communications system. The content items may include video feeds, audio feeds, television broadcasts, website, a web log or the like. Using any browser application, the user views content items presented in an interactive scroll display. Modules are included for filtering, sorting and sampling content to ensure delivery of relevant high-quality content to the user. A feedback mechanism is also included for refining relevance filtering, sorting and sampling processes.

Methods and systems for providing a customizable guide for navigating a corpus of content

Disclosed is a method of extracting informative phrases from a full corpus of documents. An index of phrases contained in the full corpus of documents is built. Then, a user specifies a subset of text to analyze. The subset may be defined as: (1) all paragraphs or sentences containing terms selected as defining a subject; (2) all documents in a category; (3) all documents written within a date range; and/or (3) all documents matching a Boolean query of terms. Once the subset is specified, it is analyzed to extract informative phrases. Specifically, the index is queried to retrieve all phrases within the subset. The number of times each of the phases occurs in the subset and in the corpus is counted. Each phrase contained in the subset is scored according to informativeness based on a comparison of a likelihood that the phrase occurs in the subset and a likelihood that the phrase occurs in the corpus as a whole. Only those phrases having an informativeness score above a predetermined value are considered highly informative and extracted.

Extracting informative phrases from unstructured text

Disclosed are embodiments of a system and a method for detecting relationships described in unstructured text-based electronic documents. The system and method incorporate the use of an input file that contains one or more text patterns that represent particular relationships. The text patterns each include regular text expressions that describe the particular relationship and slots for the location of each entity in that relationship. Document(s) are selected by a user and scanned by a proper noun tagger that identifies and tags every occurrence of proper names within the document(s). Then, a pattern matcher scans the document(s) to match text patterns. If a text pattern is matched within a document a relationship detector extracts all pairs of proper names found in the slots for each matched text pattern. The output from the relationship detector includes the names for each entity in the relationship, the type of relationship, and the identity of the document and the location of the sentence describing the relationship in the document.

Detecting relationships in unstructured text

An improved system and method for selecting and visualizing object metadata evolving over time is provided. An application may generate a visualization depicting the temporal evolution of metadata describing objects in an object store over a plurality of time intervals. The application may switch between a visualization of object metadata flowing like a river or cascading like a waterfall over time. A ranked list of metadata items may be determined for some pre-selected intervals during a pre-processing step. Then at runtime when a request may be received for providing a ranked list of metadata items for a query interval, a combination of time intervals from the pre-selected time intervals may be determined that cover the query time interval, and the ranked lists of metadata items for each time interval in the combination of time intervals that cover the query time interval may be aggregated and output for visualization.

System and method for selecting object metadata evolving over time

A sales prediction system predicts sales from online public discussions. The system utilizes manually or automatically formulated predicates to capture subsets of postings in online public discussions. The system predicts spikes in sales rank based on online chatter. The system comprises automated algorithms that predict spikes in sales rank given a time series of counts of online discussions such as blog postings. The system utilizes a stateless model of customer behavior based on a series of states of excitation that are increasingly likely to lead to a purchase decision. The stateless model of customer behavior yields a predictor of sales rank spikes that is significantly more accurate than conventional techniques operating on sales rank data alone.

Method and computer program product for predicting sales from online public discussions

System and method for visualizing the temporal evolution of object metadata

A multi-structural query system performs a high-level multi-dimensional query on a multi-structural database. The query system enables a user to navigate a search by adding restrictions incrementally. The query system uses a schema to discover structure in a multi-structural database. The query system leaves a choice of nodes to return in response to a query as a constrained set of choices available to the algorithm. The query system further casts the selection of a set of nodes as an optimization. The query system uses pairwise-disjoint collections to capture a concise set of highlights of a data set within the allowed schema. The query system further comprises efficient algorithms that yield approximately optimal solutions for several classes of objective functions.

System and method for performing a high-level multi-dimensional query on a multi-structural database

A modular scoring system using rank aggregation merges search results into an ordered list of results using many different features of documents. The ranking functions of the present system can easily be customized to the needs of a particular corpus or collection of users such as an intranet. Rank aggregation is independent of the underlying score distributions between the different factors, and can be applied to merge any set of ranking functions. Rank aggregation holds the advantage of combining the influence of many different heuristic factors in a robust way to produce high-quality results for queries. The modular scoring system combines factors such as indegree, page ranking, URL length, proximity to the root server of an intranet, etc, to form a single ordering on web pages that closely obeys the individual orderings, but also mediates between the collective wisdom of individual heuristics.

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Mountain View, CA, United States of America

Jasmine Novak