Abstract: An information processing apparatus acquires user features indicating features for each of a plurality of users and item features indicating features for each of a plurality of items, acquires time-series information indicating time-series interactions between the plurality of users and the plurality of items, constructs, based on the user features, the item features, and the time-series information, a graph including a plurality of user nodes representing the plurality of users, a plurality of item nodes representing the plurality of items, and links indicating interaction relationships in the plurality of user nodes and the plurality of item nodes, and extracts, from the graph, a node representation in the graph for any node among the plurality of user nodes and the plurality of item nodes.

Abstract: Guided character string alteration can be performed by obtaining an original character string and a plurality of altered character strings, traversing the original character string with a first Long Short Term Memory (LSTM) network to generate, for each character of the original character string, a hidden state of a partial original character string up to that character, and applying, during the traversing, an alteration learning process to each hidden state of a partial original character string to produce an alteration function for relating partial original character strings to partial altered character strings.

Abstract: A code dependency influenced bug localization apparatus and method receive bug reports and source code changes of a software program. Each source code change includes a syntax component and a location component. Each bug report includes a functional description of an aspect of the software program. The apparatus and method obtain a vectorized feature representation of each bug report, apply a learning process to the source code changes based on a code dependency among the source code changes, obtain a vectorized feature representation of each source code change based on the code dependency, merge the feature representations of the bug reports and the feature representations of the source code changes into a plurality of unified feature representations, and apply a ranking process to the unified feature representations to produce a source code relating function for relating a bug report and a source code change.

Abstract: Guided word association based domain name detection may be performed by obtaining an original domain name, constructing a feature space from a corpus of text, wherein each word appearing in the corpus is represented as a vector in the feature space, detecting whether a domain name registration exists for each combination of the original domain name and each of a plurality of seed words from the feature space, determining, for each seed word included in an existing domain name registration, a plurality of nearest neighbor candidate words, based on vector distance in the feature space, and repeating, for one or more repetitions, the detecting and the determining, wherein the plurality of nearest neighbor candidate words are utilized as the plurality of seed words.

Abstract: Guided character string alteration can be performed by obtaining an original character string and a plurality of altered character strings, traversing the original character string with a first Long Short Term Memory (LSTM) network to generate, for each character of the original character string, a hidden state of a partial original character string up to that character, and applying, during the traversing, an alteration learning process to each hidden state of a partial original character string to produce an alteration function for relating partial original character strings to partial altered character strings.

Abstract: Guided word association based domain name detection may be performed by obtaining an original domain name, constructing a feature space from a corpus of text, wherein each word appearing in the corpus is represented as a vector in the feature space, detecting whether a domain name registration exists for each combination of the original domain name and each of a plurality of seed words from the feature space, determining, for each seed word included in an existing domain name registration, a plurality of nearest neighbor candidate words, based on vector distance in the feature space, and repeating, for one or more repetitions, the detecting and the determining, wherein the plurality of nearest neighbor candidate words are utilized as the plurality of seed words.

Abstract: A code dependency influenced bug localization apparatus and method receive bug reports and source code changes of a software program. Each source code change includes a syntax component and a location component. Each bug report includes a functional description of an aspect of the software program. The apparatus and method obtain a vectorized feature representation of each bug report, apply a learning process to the source code changes based on a code dependency among the source code changes, obtain a vectorized feature representation of each source code change based on the code dependency, merge the feature representations of the bug reports and the feature representations of the source code changes into a plurality of unified feature representations, and apply a ranking process to the unified feature representations to produce a source code relating function for relating a bug report and a source code change.